program(1.0)
[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3520.4.1"}, {"coremlc-version", "3520.5.1"}})]
{
    func main<ios16>(tensor<fp32, [1, 77]> input_ids) {
            tensor<int32, []> var_5 = const()[name = tensor<string, []>("op_5"), val = tensor<int32, []>(-1)];
            tensor<string, []> cast_1_dtype_0 = const()[name = tensor<string, []>("cast_1_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> inputs_embeds_axis_0 = const()[name = tensor<string, []>("inputs_embeds_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> inputs_embeds_batch_dims_0 = const()[name = tensor<string, []>("inputs_embeds_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<fp16, [49408, 1280]> text_encoder_text_model_embeddings_token_embedding_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [47431680]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47431808))), name = tensor<string, []>("text_encoder_text_model_embeddings_token_embedding_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([49408, 1280])];
            tensor<int32, [1, 77]> cast_1 = cast(dtype = cast_1_dtype_0, x = input_ids)[name = tensor<string, []>("cast_2")];
            tensor<fp16, [1, 77, 1280]> inputs_embeds_cast_fp16 = gather(axis = inputs_embeds_axis_0, batch_dims = inputs_embeds_batch_dims_0, indices = cast_1, x = text_encoder_text_model_embeddings_token_embedding_weight_to_fp16_palettized)[name = tensor<string, []>("inputs_embeds_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> position_embeddings_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [73920]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47432000))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47505984))), name = tensor<string, []>("position_embeddings_to_fp16_palettized"), shape = tensor<uint32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 1280]> input_3_cast_fp16 = add(x = inputs_embeds_cast_fp16, y = position_embeddings_to_fp16_palettized)[name = tensor<string, []>("input_3_cast_fp16")];
            tensor<int32, [1]> hidden_states_1_axes_0 = const()[name = tensor<string, []>("hidden_states_1_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47506176)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47508800)))];
            tensor<fp16, []> var_15_to_fp16 = const()[name = tensor<string, []>("op_15_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 77, 1280]> hidden_states_1_cast_fp16 = layer_norm(axes = hidden_states_1_axes_0, beta = text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16, x = input_3_cast_fp16)[name = tensor<string, []>("hidden_states_1_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47511424))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48740288))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48740480)))];
            tensor<fp16, [1, 77, 1280]> linear_0_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_1_cast_fp16)[name = tensor<string, []>("linear_0_cast_fp16")];
            tensor<fp16, []> var_148_to_fp16 = const()[name = tensor<string, []>("op_148_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_5_cast_fp16 = mul(x = linear_0_cast_fp16, y = var_148_to_fp16)[name = tensor<string, []>("tensor_5_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48743104))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(49971968))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(49972160)))];
            tensor<fp16, [1, 77, 1280]> linear_1_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_1_cast_fp16)[name = tensor<string, []>("linear_1_cast_fp16")];
            tensor<int32, [4]> var_153 = const()[name = tensor<string, []>("op_153"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_154_cast_fp16 = reshape(shape = var_153, x = linear_1_cast_fp16)[name = tensor<string, []>("op_154_cast_fp16")];
            tensor<int32, [4]> var_155_perm_0 = const()[name = tensor<string, []>("op_155_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(49974784))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(51203648))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(51203840)))];
            tensor<fp16, [1, 77, 1280]> linear_2_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_1_cast_fp16)[name = tensor<string, []>("linear_2_cast_fp16")];
            tensor<int32, [4]> var_160 = const()[name = tensor<string, []>("op_160"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_161_cast_fp16 = reshape(shape = var_160, x = linear_2_cast_fp16)[name = tensor<string, []>("op_161_cast_fp16")];
            tensor<int32, [4]> var_162_perm_0 = const()[name = tensor<string, []>("op_162_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_169 = const()[name = tensor<string, []>("op_169"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_170_cast_fp16 = reshape(shape = var_169, x = tensor_5_cast_fp16)[name = tensor<string, []>("op_170_cast_fp16")];
            tensor<int32, [4]> var_171_perm_0 = const()[name = tensor<string, []>("op_171_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_173 = const()[name = tensor<string, []>("op_173"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_171_cast_fp16 = transpose(perm = var_171_perm_0, x = var_170_cast_fp16)[name = tensor<string, []>("transpose_127")];
            tensor<fp16, [20, 77, 64]> query_states_1_cast_fp16 = reshape(shape = var_173, x = var_171_cast_fp16)[name = tensor<string, []>("query_states_1_cast_fp16")];
            tensor<int32, [3]> var_175 = const()[name = tensor<string, []>("op_175"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_155_cast_fp16 = transpose(perm = var_155_perm_0, x = var_154_cast_fp16)[name = tensor<string, []>("transpose_126")];
            tensor<fp16, [20, 77, 64]> key_states_3_cast_fp16 = reshape(shape = var_175, x = var_155_cast_fp16)[name = tensor<string, []>("key_states_3_cast_fp16")];
            tensor<int32, [3]> var_177 = const()[name = tensor<string, []>("op_177"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_162_cast_fp16 = transpose(perm = var_162_perm_0, x = var_161_cast_fp16)[name = tensor<string, []>("transpose_125")];
            tensor<fp16, [20, 77, 64]> value_states_3_cast_fp16 = reshape(shape = var_177, x = var_162_cast_fp16)[name = tensor<string, []>("value_states_3_cast_fp16")];
            tensor<bool, []> attn_weights_1_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_1_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_1_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_1_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_1_cast_fp16 = matmul(transpose_x = attn_weights_1_transpose_x_1, transpose_y = attn_weights_1_transpose_y_1, x = query_states_1_cast_fp16, y = key_states_3_cast_fp16)[name = tensor<string, []>("attn_weights_1_cast_fp16")];
            tensor<int32, [4]> var_182 = const()[name = tensor<string, []>("op_182"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_183_cast_fp16 = reshape(shape = var_182, x = attn_weights_1_cast_fp16)[name = tensor<string, []>("op_183_cast_fp16")];
            tensor<fp16, [1, 1, 77, 77]> op_58_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4447]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(51206464))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(51211008))), name = tensor<string, []>("op_58_to_fp16_palettized"), shape = tensor<uint32, [4]>([1, 1, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_3_cast_fp16 = add(x = var_183_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_3_cast_fp16")];
            tensor<int32, [3]> var_188 = const()[name = tensor<string, []>("op_188"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_5_cast_fp16 = reshape(shape = var_188, x = attn_weights_3_cast_fp16)[name = tensor<string, []>("input_5_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_7_cast_fp16 = softmax(axis = var_5, x = input_5_cast_fp16)[name = tensor<string, []>("input_7_cast_fp16")];
            tensor<bool, []> attn_output_1_transpose_x_0 = const()[name = tensor<string, []>("attn_output_1_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_1_transpose_y_0 = const()[name = tensor<string, []>("attn_output_1_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_1_cast_fp16 = matmul(transpose_x = attn_output_1_transpose_x_0, transpose_y = attn_output_1_transpose_y_0, x = input_7_cast_fp16, y = value_states_3_cast_fp16)[name = tensor<string, []>("attn_output_1_cast_fp16")];
            tensor<int32, [4]> var_193 = const()[name = tensor<string, []>("op_193"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_3_cast_fp16 = reshape(shape = var_193, x = attn_output_1_cast_fp16)[name = tensor<string, []>("attn_output_3_cast_fp16")];
            tensor<int32, [4]> attn_output_5_perm_0 = const()[name = tensor<string, []>("attn_output_5_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_196 = const()[name = tensor<string, []>("op_196"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_5_cast_fp16 = transpose(perm = attn_output_5_perm_0, x = attn_output_3_cast_fp16)[name = tensor<string, []>("transpose_124")];
            tensor<fp16, [1, 77, 1280]> input_9_cast_fp16 = reshape(shape = var_196, x = attn_output_5_cast_fp16)[name = tensor<string, []>("input_9_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(51211200))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(52440064))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(52440256)))];
            tensor<fp16, [1, 77, 1280]> linear_3_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized, x = input_9_cast_fp16)[name = tensor<string, []>("linear_3_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_11_cast_fp16 = add(x = input_3_cast_fp16, y = linear_3_cast_fp16)[name = tensor<string, []>("input_11_cast_fp16")];
            tensor<int32, [1]> input_13_axes_0 = const()[name = tensor<string, []>("input_13_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(52442880)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(52445504)))];
            tensor<fp16, [1, 77, 1280]> input_13_cast_fp16 = layer_norm(axes = input_13_axes_0, beta = text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16, x = input_11_cast_fp16)[name = tensor<string, []>("input_13_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(52448128))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57363392))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57363584)))];
            tensor<fp16, [1, 77, 5120]> linear_4_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized, x = input_13_cast_fp16)[name = tensor<string, []>("linear_4_cast_fp16")];
            tensor<string, []> input_17_mode_0 = const()[name = tensor<string, []>("input_17_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_17_cast_fp16 = gelu(mode = input_17_mode_0, x = linear_4_cast_fp16)[name = tensor<string, []>("input_17_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57373888))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(62289152))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(62289344)))];
            tensor<fp16, [1, 77, 1280]> linear_5_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized, x = input_17_cast_fp16)[name = tensor<string, []>("linear_5_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_19_cast_fp16 = add(x = input_11_cast_fp16, y = linear_5_cast_fp16)[name = tensor<string, []>("input_19_cast_fp16")];
            tensor<int32, [1]> hidden_states_7_axes_0 = const()[name = tensor<string, []>("hidden_states_7_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(62291968)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(62294592)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_7_cast_fp16 = layer_norm(axes = hidden_states_7_axes_0, beta = text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16, x = input_19_cast_fp16)[name = tensor<string, []>("hidden_states_7_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(62297216))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(63526080))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(63526272)))];
            tensor<fp16, [1, 77, 1280]> linear_6_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_7_cast_fp16)[name = tensor<string, []>("linear_6_cast_fp16")];
            tensor<fp16, []> var_235_to_fp16 = const()[name = tensor<string, []>("op_235_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_11_cast_fp16 = mul(x = linear_6_cast_fp16, y = var_235_to_fp16)[name = tensor<string, []>("tensor_11_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(63528896))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64757760))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64757952)))];
            tensor<fp16, [1, 77, 1280]> linear_7_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_7_cast_fp16)[name = tensor<string, []>("linear_7_cast_fp16")];
            tensor<int32, [4]> var_240 = const()[name = tensor<string, []>("op_240"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_241_cast_fp16 = reshape(shape = var_240, x = linear_7_cast_fp16)[name = tensor<string, []>("op_241_cast_fp16")];
            tensor<int32, [4]> var_242_perm_0 = const()[name = tensor<string, []>("op_242_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64760576))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(65989440))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(65989632)))];
            tensor<fp16, [1, 77, 1280]> linear_8_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_7_cast_fp16)[name = tensor<string, []>("linear_8_cast_fp16")];
            tensor<int32, [4]> var_247 = const()[name = tensor<string, []>("op_247"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_248_cast_fp16 = reshape(shape = var_247, x = linear_8_cast_fp16)[name = tensor<string, []>("op_248_cast_fp16")];
            tensor<int32, [4]> var_249_perm_0 = const()[name = tensor<string, []>("op_249_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_256 = const()[name = tensor<string, []>("op_256"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_257_cast_fp16 = reshape(shape = var_256, x = tensor_11_cast_fp16)[name = tensor<string, []>("op_257_cast_fp16")];
            tensor<int32, [4]> var_258_perm_0 = const()[name = tensor<string, []>("op_258_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_260 = const()[name = tensor<string, []>("op_260"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_258_cast_fp16 = transpose(perm = var_258_perm_0, x = var_257_cast_fp16)[name = tensor<string, []>("transpose_123")];
            tensor<fp16, [20, 77, 64]> query_states_3_cast_fp16 = reshape(shape = var_260, x = var_258_cast_fp16)[name = tensor<string, []>("query_states_3_cast_fp16")];
            tensor<int32, [3]> var_262 = const()[name = tensor<string, []>("op_262"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_242_cast_fp16 = transpose(perm = var_242_perm_0, x = var_241_cast_fp16)[name = tensor<string, []>("transpose_122")];
            tensor<fp16, [20, 77, 64]> key_states_7_cast_fp16 = reshape(shape = var_262, x = var_242_cast_fp16)[name = tensor<string, []>("key_states_7_cast_fp16")];
            tensor<int32, [3]> var_264 = const()[name = tensor<string, []>("op_264"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_249_cast_fp16 = transpose(perm = var_249_perm_0, x = var_248_cast_fp16)[name = tensor<string, []>("transpose_121")];
            tensor<fp16, [20, 77, 64]> value_states_7_cast_fp16 = reshape(shape = var_264, x = var_249_cast_fp16)[name = tensor<string, []>("value_states_7_cast_fp16")];
            tensor<bool, []> attn_weights_7_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_7_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_7_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_7_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_7_cast_fp16 = matmul(transpose_x = attn_weights_7_transpose_x_1, transpose_y = attn_weights_7_transpose_y_1, x = query_states_3_cast_fp16, y = key_states_7_cast_fp16)[name = tensor<string, []>("attn_weights_7_cast_fp16")];
            tensor<int32, [4]> var_269 = const()[name = tensor<string, []>("op_269"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_270_cast_fp16 = reshape(shape = var_269, x = attn_weights_7_cast_fp16)[name = tensor<string, []>("op_270_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_9_cast_fp16 = add(x = var_270_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_9_cast_fp16")];
            tensor<int32, [3]> var_275 = const()[name = tensor<string, []>("op_275"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_21_cast_fp16 = reshape(shape = var_275, x = attn_weights_9_cast_fp16)[name = tensor<string, []>("input_21_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_23_cast_fp16 = softmax(axis = var_5, x = input_21_cast_fp16)[name = tensor<string, []>("input_23_cast_fp16")];
            tensor<bool, []> attn_output_7_transpose_x_0 = const()[name = tensor<string, []>("attn_output_7_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_7_transpose_y_0 = const()[name = tensor<string, []>("attn_output_7_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_7_cast_fp16 = matmul(transpose_x = attn_output_7_transpose_x_0, transpose_y = attn_output_7_transpose_y_0, x = input_23_cast_fp16, y = value_states_7_cast_fp16)[name = tensor<string, []>("attn_output_7_cast_fp16")];
            tensor<int32, [4]> var_280 = const()[name = tensor<string, []>("op_280"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_9_cast_fp16 = reshape(shape = var_280, x = attn_output_7_cast_fp16)[name = tensor<string, []>("attn_output_9_cast_fp16")];
            tensor<int32, [4]> attn_output_11_perm_0 = const()[name = tensor<string, []>("attn_output_11_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_283 = const()[name = tensor<string, []>("op_283"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_11_cast_fp16 = transpose(perm = attn_output_11_perm_0, x = attn_output_9_cast_fp16)[name = tensor<string, []>("transpose_120")];
            tensor<fp16, [1, 77, 1280]> input_25_cast_fp16 = reshape(shape = var_283, x = attn_output_11_cast_fp16)[name = tensor<string, []>("input_25_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(65992256))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(67221120))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(67221312)))];
            tensor<fp16, [1, 77, 1280]> linear_9_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized, x = input_25_cast_fp16)[name = tensor<string, []>("linear_9_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_27_cast_fp16 = add(x = input_19_cast_fp16, y = linear_9_cast_fp16)[name = tensor<string, []>("input_27_cast_fp16")];
            tensor<int32, [1]> input_29_axes_0 = const()[name = tensor<string, []>("input_29_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(67223936)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(67226560)))];
            tensor<fp16, [1, 77, 1280]> input_29_cast_fp16 = layer_norm(axes = input_29_axes_0, beta = text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16, x = input_27_cast_fp16)[name = tensor<string, []>("input_29_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(67229184))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(72144448))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(72144640)))];
            tensor<fp16, [1, 77, 5120]> linear_10_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized, x = input_29_cast_fp16)[name = tensor<string, []>("linear_10_cast_fp16")];
            tensor<string, []> input_33_mode_0 = const()[name = tensor<string, []>("input_33_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_33_cast_fp16 = gelu(mode = input_33_mode_0, x = linear_10_cast_fp16)[name = tensor<string, []>("input_33_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(72154944))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77070208))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77070400)))];
            tensor<fp16, [1, 77, 1280]> linear_11_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized, x = input_33_cast_fp16)[name = tensor<string, []>("linear_11_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_35_cast_fp16 = add(x = input_27_cast_fp16, y = linear_11_cast_fp16)[name = tensor<string, []>("input_35_cast_fp16")];
            tensor<int32, [1]> hidden_states_13_axes_0 = const()[name = tensor<string, []>("hidden_states_13_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77073024)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77075648)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_13_cast_fp16 = layer_norm(axes = hidden_states_13_axes_0, beta = text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16, x = input_35_cast_fp16)[name = tensor<string, []>("hidden_states_13_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77078272))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78307136))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78307328)))];
            tensor<fp16, [1, 77, 1280]> linear_12_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_13_cast_fp16)[name = tensor<string, []>("linear_12_cast_fp16")];
            tensor<fp16, []> var_322_to_fp16 = const()[name = tensor<string, []>("op_322_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_17_cast_fp16 = mul(x = linear_12_cast_fp16, y = var_322_to_fp16)[name = tensor<string, []>("tensor_17_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78309952))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(79538816))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(79539008)))];
            tensor<fp16, [1, 77, 1280]> linear_13_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_13_cast_fp16)[name = tensor<string, []>("linear_13_cast_fp16")];
            tensor<int32, [4]> var_327 = const()[name = tensor<string, []>("op_327"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_328_cast_fp16 = reshape(shape = var_327, x = linear_13_cast_fp16)[name = tensor<string, []>("op_328_cast_fp16")];
            tensor<int32, [4]> var_329_perm_0 = const()[name = tensor<string, []>("op_329_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(79541632))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(80770496))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(80770688)))];
            tensor<fp16, [1, 77, 1280]> linear_14_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_13_cast_fp16)[name = tensor<string, []>("linear_14_cast_fp16")];
            tensor<int32, [4]> var_334 = const()[name = tensor<string, []>("op_334"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_335_cast_fp16 = reshape(shape = var_334, x = linear_14_cast_fp16)[name = tensor<string, []>("op_335_cast_fp16")];
            tensor<int32, [4]> var_336_perm_0 = const()[name = tensor<string, []>("op_336_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_343 = const()[name = tensor<string, []>("op_343"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_344_cast_fp16 = reshape(shape = var_343, x = tensor_17_cast_fp16)[name = tensor<string, []>("op_344_cast_fp16")];
            tensor<int32, [4]> var_345_perm_0 = const()[name = tensor<string, []>("op_345_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_347 = const()[name = tensor<string, []>("op_347"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_345_cast_fp16 = transpose(perm = var_345_perm_0, x = var_344_cast_fp16)[name = tensor<string, []>("transpose_119")];
            tensor<fp16, [20, 77, 64]> query_states_5_cast_fp16 = reshape(shape = var_347, x = var_345_cast_fp16)[name = tensor<string, []>("query_states_5_cast_fp16")];
            tensor<int32, [3]> var_349 = const()[name = tensor<string, []>("op_349"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_329_cast_fp16 = transpose(perm = var_329_perm_0, x = var_328_cast_fp16)[name = tensor<string, []>("transpose_118")];
            tensor<fp16, [20, 77, 64]> key_states_11_cast_fp16 = reshape(shape = var_349, x = var_329_cast_fp16)[name = tensor<string, []>("key_states_11_cast_fp16")];
            tensor<int32, [3]> var_351 = const()[name = tensor<string, []>("op_351"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_336_cast_fp16 = transpose(perm = var_336_perm_0, x = var_335_cast_fp16)[name = tensor<string, []>("transpose_117")];
            tensor<fp16, [20, 77, 64]> value_states_11_cast_fp16 = reshape(shape = var_351, x = var_336_cast_fp16)[name = tensor<string, []>("value_states_11_cast_fp16")];
            tensor<bool, []> attn_weights_13_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_13_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_13_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_13_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_13_cast_fp16 = matmul(transpose_x = attn_weights_13_transpose_x_1, transpose_y = attn_weights_13_transpose_y_1, x = query_states_5_cast_fp16, y = key_states_11_cast_fp16)[name = tensor<string, []>("attn_weights_13_cast_fp16")];
            tensor<int32, [4]> var_356 = const()[name = tensor<string, []>("op_356"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_357_cast_fp16 = reshape(shape = var_356, x = attn_weights_13_cast_fp16)[name = tensor<string, []>("op_357_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_15_cast_fp16 = add(x = var_357_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_15_cast_fp16")];
            tensor<int32, [3]> var_362 = const()[name = tensor<string, []>("op_362"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_37_cast_fp16 = reshape(shape = var_362, x = attn_weights_15_cast_fp16)[name = tensor<string, []>("input_37_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_39_cast_fp16 = softmax(axis = var_5, x = input_37_cast_fp16)[name = tensor<string, []>("input_39_cast_fp16")];
            tensor<bool, []> attn_output_13_transpose_x_0 = const()[name = tensor<string, []>("attn_output_13_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_13_transpose_y_0 = const()[name = tensor<string, []>("attn_output_13_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_13_cast_fp16 = matmul(transpose_x = attn_output_13_transpose_x_0, transpose_y = attn_output_13_transpose_y_0, x = input_39_cast_fp16, y = value_states_11_cast_fp16)[name = tensor<string, []>("attn_output_13_cast_fp16")];
            tensor<int32, [4]> var_367 = const()[name = tensor<string, []>("op_367"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_15_cast_fp16 = reshape(shape = var_367, x = attn_output_13_cast_fp16)[name = tensor<string, []>("attn_output_15_cast_fp16")];
            tensor<int32, [4]> attn_output_17_perm_0 = const()[name = tensor<string, []>("attn_output_17_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_370 = const()[name = tensor<string, []>("op_370"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_17_cast_fp16 = transpose(perm = attn_output_17_perm_0, x = attn_output_15_cast_fp16)[name = tensor<string, []>("transpose_116")];
            tensor<fp16, [1, 77, 1280]> input_41_cast_fp16 = reshape(shape = var_370, x = attn_output_17_cast_fp16)[name = tensor<string, []>("input_41_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(80773312))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(82002176))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(82002368)))];
            tensor<fp16, [1, 77, 1280]> linear_15_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized, x = input_41_cast_fp16)[name = tensor<string, []>("linear_15_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_43_cast_fp16 = add(x = input_35_cast_fp16, y = linear_15_cast_fp16)[name = tensor<string, []>("input_43_cast_fp16")];
            tensor<int32, [1]> input_45_axes_0 = const()[name = tensor<string, []>("input_45_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(82004992)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(82007616)))];
            tensor<fp16, [1, 77, 1280]> input_45_cast_fp16 = layer_norm(axes = input_45_axes_0, beta = text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16, x = input_43_cast_fp16)[name = tensor<string, []>("input_45_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(82010240))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(86925504))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(86925696)))];
            tensor<fp16, [1, 77, 5120]> linear_16_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized, x = input_45_cast_fp16)[name = tensor<string, []>("linear_16_cast_fp16")];
            tensor<string, []> input_49_mode_0 = const()[name = tensor<string, []>("input_49_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_49_cast_fp16 = gelu(mode = input_49_mode_0, x = linear_16_cast_fp16)[name = tensor<string, []>("input_49_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(86936000))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(91851264))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(91851456)))];
            tensor<fp16, [1, 77, 1280]> linear_17_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized, x = input_49_cast_fp16)[name = tensor<string, []>("linear_17_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_51_cast_fp16 = add(x = input_43_cast_fp16, y = linear_17_cast_fp16)[name = tensor<string, []>("input_51_cast_fp16")];
            tensor<int32, [1]> hidden_states_19_axes_0 = const()[name = tensor<string, []>("hidden_states_19_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(91854080)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(91856704)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_19_cast_fp16 = layer_norm(axes = hidden_states_19_axes_0, beta = text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16, x = input_51_cast_fp16)[name = tensor<string, []>("hidden_states_19_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(91859328))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(93088192))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(93088384)))];
            tensor<fp16, [1, 77, 1280]> linear_18_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_19_cast_fp16)[name = tensor<string, []>("linear_18_cast_fp16")];
            tensor<fp16, []> var_409_to_fp16 = const()[name = tensor<string, []>("op_409_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_23_cast_fp16 = mul(x = linear_18_cast_fp16, y = var_409_to_fp16)[name = tensor<string, []>("tensor_23_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(93091008))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(94319872))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(94320064)))];
            tensor<fp16, [1, 77, 1280]> linear_19_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_19_cast_fp16)[name = tensor<string, []>("linear_19_cast_fp16")];
            tensor<int32, [4]> var_414 = const()[name = tensor<string, []>("op_414"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_415_cast_fp16 = reshape(shape = var_414, x = linear_19_cast_fp16)[name = tensor<string, []>("op_415_cast_fp16")];
            tensor<int32, [4]> var_416_perm_0 = const()[name = tensor<string, []>("op_416_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(94322688))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95551552))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95551744)))];
            tensor<fp16, [1, 77, 1280]> linear_20_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_19_cast_fp16)[name = tensor<string, []>("linear_20_cast_fp16")];
            tensor<int32, [4]> var_421 = const()[name = tensor<string, []>("op_421"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_422_cast_fp16 = reshape(shape = var_421, x = linear_20_cast_fp16)[name = tensor<string, []>("op_422_cast_fp16")];
            tensor<int32, [4]> var_423_perm_0 = const()[name = tensor<string, []>("op_423_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_430 = const()[name = tensor<string, []>("op_430"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_431_cast_fp16 = reshape(shape = var_430, x = tensor_23_cast_fp16)[name = tensor<string, []>("op_431_cast_fp16")];
            tensor<int32, [4]> var_432_perm_0 = const()[name = tensor<string, []>("op_432_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_434 = const()[name = tensor<string, []>("op_434"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_432_cast_fp16 = transpose(perm = var_432_perm_0, x = var_431_cast_fp16)[name = tensor<string, []>("transpose_115")];
            tensor<fp16, [20, 77, 64]> query_states_7_cast_fp16 = reshape(shape = var_434, x = var_432_cast_fp16)[name = tensor<string, []>("query_states_7_cast_fp16")];
            tensor<int32, [3]> var_436 = const()[name = tensor<string, []>("op_436"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_416_cast_fp16 = transpose(perm = var_416_perm_0, x = var_415_cast_fp16)[name = tensor<string, []>("transpose_114")];
            tensor<fp16, [20, 77, 64]> key_states_15_cast_fp16 = reshape(shape = var_436, x = var_416_cast_fp16)[name = tensor<string, []>("key_states_15_cast_fp16")];
            tensor<int32, [3]> var_438 = const()[name = tensor<string, []>("op_438"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_423_cast_fp16 = transpose(perm = var_423_perm_0, x = var_422_cast_fp16)[name = tensor<string, []>("transpose_113")];
            tensor<fp16, [20, 77, 64]> value_states_15_cast_fp16 = reshape(shape = var_438, x = var_423_cast_fp16)[name = tensor<string, []>("value_states_15_cast_fp16")];
            tensor<bool, []> attn_weights_19_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_19_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_19_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_19_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_19_cast_fp16 = matmul(transpose_x = attn_weights_19_transpose_x_1, transpose_y = attn_weights_19_transpose_y_1, x = query_states_7_cast_fp16, y = key_states_15_cast_fp16)[name = tensor<string, []>("attn_weights_19_cast_fp16")];
            tensor<int32, [4]> var_443 = const()[name = tensor<string, []>("op_443"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_444_cast_fp16 = reshape(shape = var_443, x = attn_weights_19_cast_fp16)[name = tensor<string, []>("op_444_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_21_cast_fp16 = add(x = var_444_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_21_cast_fp16")];
            tensor<int32, [3]> var_449 = const()[name = tensor<string, []>("op_449"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_53_cast_fp16 = reshape(shape = var_449, x = attn_weights_21_cast_fp16)[name = tensor<string, []>("input_53_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_55_cast_fp16 = softmax(axis = var_5, x = input_53_cast_fp16)[name = tensor<string, []>("input_55_cast_fp16")];
            tensor<bool, []> attn_output_19_transpose_x_0 = const()[name = tensor<string, []>("attn_output_19_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_19_transpose_y_0 = const()[name = tensor<string, []>("attn_output_19_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_19_cast_fp16 = matmul(transpose_x = attn_output_19_transpose_x_0, transpose_y = attn_output_19_transpose_y_0, x = input_55_cast_fp16, y = value_states_15_cast_fp16)[name = tensor<string, []>("attn_output_19_cast_fp16")];
            tensor<int32, [4]> var_454 = const()[name = tensor<string, []>("op_454"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_21_cast_fp16 = reshape(shape = var_454, x = attn_output_19_cast_fp16)[name = tensor<string, []>("attn_output_21_cast_fp16")];
            tensor<int32, [4]> attn_output_23_perm_0 = const()[name = tensor<string, []>("attn_output_23_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_457 = const()[name = tensor<string, []>("op_457"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_23_cast_fp16 = transpose(perm = attn_output_23_perm_0, x = attn_output_21_cast_fp16)[name = tensor<string, []>("transpose_112")];
            tensor<fp16, [1, 77, 1280]> input_57_cast_fp16 = reshape(shape = var_457, x = attn_output_23_cast_fp16)[name = tensor<string, []>("input_57_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95554368))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(96783232))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(96783424)))];
            tensor<fp16, [1, 77, 1280]> linear_21_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized, x = input_57_cast_fp16)[name = tensor<string, []>("linear_21_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_59_cast_fp16 = add(x = input_51_cast_fp16, y = linear_21_cast_fp16)[name = tensor<string, []>("input_59_cast_fp16")];
            tensor<int32, [1]> input_61_axes_0 = const()[name = tensor<string, []>("input_61_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(96786048)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(96788672)))];
            tensor<fp16, [1, 77, 1280]> input_61_cast_fp16 = layer_norm(axes = input_61_axes_0, beta = text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16, x = input_59_cast_fp16)[name = tensor<string, []>("input_61_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(96791296))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(101706560))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(101706752)))];
            tensor<fp16, [1, 77, 5120]> linear_22_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized, x = input_61_cast_fp16)[name = tensor<string, []>("linear_22_cast_fp16")];
            tensor<string, []> input_65_mode_0 = const()[name = tensor<string, []>("input_65_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_65_cast_fp16 = gelu(mode = input_65_mode_0, x = linear_22_cast_fp16)[name = tensor<string, []>("input_65_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(101717056))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(106632320))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(106632512)))];
            tensor<fp16, [1, 77, 1280]> linear_23_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized, x = input_65_cast_fp16)[name = tensor<string, []>("linear_23_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_67_cast_fp16 = add(x = input_59_cast_fp16, y = linear_23_cast_fp16)[name = tensor<string, []>("input_67_cast_fp16")];
            tensor<int32, [1]> hidden_states_25_axes_0 = const()[name = tensor<string, []>("hidden_states_25_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(106635136)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(106637760)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_25_cast_fp16 = layer_norm(axes = hidden_states_25_axes_0, beta = text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16, x = input_67_cast_fp16)[name = tensor<string, []>("hidden_states_25_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(106640384))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(107869248))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(107869440)))];
            tensor<fp16, [1, 77, 1280]> linear_24_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_25_cast_fp16)[name = tensor<string, []>("linear_24_cast_fp16")];
            tensor<fp16, []> var_496_to_fp16 = const()[name = tensor<string, []>("op_496_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_29_cast_fp16 = mul(x = linear_24_cast_fp16, y = var_496_to_fp16)[name = tensor<string, []>("tensor_29_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(107872064))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(109100928))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(109101120)))];
            tensor<fp16, [1, 77, 1280]> linear_25_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_25_cast_fp16)[name = tensor<string, []>("linear_25_cast_fp16")];
            tensor<int32, [4]> var_501 = const()[name = tensor<string, []>("op_501"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_502_cast_fp16 = reshape(shape = var_501, x = linear_25_cast_fp16)[name = tensor<string, []>("op_502_cast_fp16")];
            tensor<int32, [4]> var_503_perm_0 = const()[name = tensor<string, []>("op_503_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(109103744))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(110332608))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(110332800)))];
            tensor<fp16, [1, 77, 1280]> linear_26_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_25_cast_fp16)[name = tensor<string, []>("linear_26_cast_fp16")];
            tensor<int32, [4]> var_508 = const()[name = tensor<string, []>("op_508"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_509_cast_fp16 = reshape(shape = var_508, x = linear_26_cast_fp16)[name = tensor<string, []>("op_509_cast_fp16")];
            tensor<int32, [4]> var_510_perm_0 = const()[name = tensor<string, []>("op_510_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_517 = const()[name = tensor<string, []>("op_517"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_518_cast_fp16 = reshape(shape = var_517, x = tensor_29_cast_fp16)[name = tensor<string, []>("op_518_cast_fp16")];
            tensor<int32, [4]> var_519_perm_0 = const()[name = tensor<string, []>("op_519_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_521 = const()[name = tensor<string, []>("op_521"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_519_cast_fp16 = transpose(perm = var_519_perm_0, x = var_518_cast_fp16)[name = tensor<string, []>("transpose_111")];
            tensor<fp16, [20, 77, 64]> query_states_9_cast_fp16 = reshape(shape = var_521, x = var_519_cast_fp16)[name = tensor<string, []>("query_states_9_cast_fp16")];
            tensor<int32, [3]> var_523 = const()[name = tensor<string, []>("op_523"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_503_cast_fp16 = transpose(perm = var_503_perm_0, x = var_502_cast_fp16)[name = tensor<string, []>("transpose_110")];
            tensor<fp16, [20, 77, 64]> key_states_19_cast_fp16 = reshape(shape = var_523, x = var_503_cast_fp16)[name = tensor<string, []>("key_states_19_cast_fp16")];
            tensor<int32, [3]> var_525 = const()[name = tensor<string, []>("op_525"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_510_cast_fp16 = transpose(perm = var_510_perm_0, x = var_509_cast_fp16)[name = tensor<string, []>("transpose_109")];
            tensor<fp16, [20, 77, 64]> value_states_19_cast_fp16 = reshape(shape = var_525, x = var_510_cast_fp16)[name = tensor<string, []>("value_states_19_cast_fp16")];
            tensor<bool, []> attn_weights_25_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_25_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_25_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_25_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_25_cast_fp16 = matmul(transpose_x = attn_weights_25_transpose_x_1, transpose_y = attn_weights_25_transpose_y_1, x = query_states_9_cast_fp16, y = key_states_19_cast_fp16)[name = tensor<string, []>("attn_weights_25_cast_fp16")];
            tensor<int32, [4]> var_530 = const()[name = tensor<string, []>("op_530"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_531_cast_fp16 = reshape(shape = var_530, x = attn_weights_25_cast_fp16)[name = tensor<string, []>("op_531_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_27_cast_fp16 = add(x = var_531_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_27_cast_fp16")];
            tensor<int32, [3]> var_536 = const()[name = tensor<string, []>("op_536"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_69_cast_fp16 = reshape(shape = var_536, x = attn_weights_27_cast_fp16)[name = tensor<string, []>("input_69_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_71_cast_fp16 = softmax(axis = var_5, x = input_69_cast_fp16)[name = tensor<string, []>("input_71_cast_fp16")];
            tensor<bool, []> attn_output_25_transpose_x_0 = const()[name = tensor<string, []>("attn_output_25_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_25_transpose_y_0 = const()[name = tensor<string, []>("attn_output_25_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_25_cast_fp16 = matmul(transpose_x = attn_output_25_transpose_x_0, transpose_y = attn_output_25_transpose_y_0, x = input_71_cast_fp16, y = value_states_19_cast_fp16)[name = tensor<string, []>("attn_output_25_cast_fp16")];
            tensor<int32, [4]> var_541 = const()[name = tensor<string, []>("op_541"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_27_cast_fp16 = reshape(shape = var_541, x = attn_output_25_cast_fp16)[name = tensor<string, []>("attn_output_27_cast_fp16")];
            tensor<int32, [4]> attn_output_29_perm_0 = const()[name = tensor<string, []>("attn_output_29_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_544 = const()[name = tensor<string, []>("op_544"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_29_cast_fp16 = transpose(perm = attn_output_29_perm_0, x = attn_output_27_cast_fp16)[name = tensor<string, []>("transpose_108")];
            tensor<fp16, [1, 77, 1280]> input_73_cast_fp16 = reshape(shape = var_544, x = attn_output_29_cast_fp16)[name = tensor<string, []>("input_73_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(110335424))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(111564288))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(111564480)))];
            tensor<fp16, [1, 77, 1280]> linear_27_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized, x = input_73_cast_fp16)[name = tensor<string, []>("linear_27_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_75_cast_fp16 = add(x = input_67_cast_fp16, y = linear_27_cast_fp16)[name = tensor<string, []>("input_75_cast_fp16")];
            tensor<int32, [1]> input_77_axes_0 = const()[name = tensor<string, []>("input_77_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(111567104)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(111569728)))];
            tensor<fp16, [1, 77, 1280]> input_77_cast_fp16 = layer_norm(axes = input_77_axes_0, beta = text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16, x = input_75_cast_fp16)[name = tensor<string, []>("input_77_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(111572352))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(116487616))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(116487808)))];
            tensor<fp16, [1, 77, 5120]> linear_28_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized, x = input_77_cast_fp16)[name = tensor<string, []>("linear_28_cast_fp16")];
            tensor<string, []> input_81_mode_0 = const()[name = tensor<string, []>("input_81_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_81_cast_fp16 = gelu(mode = input_81_mode_0, x = linear_28_cast_fp16)[name = tensor<string, []>("input_81_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(116498112))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(121413376))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(121413568)))];
            tensor<fp16, [1, 77, 1280]> linear_29_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized, x = input_81_cast_fp16)[name = tensor<string, []>("linear_29_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_83_cast_fp16 = add(x = input_75_cast_fp16, y = linear_29_cast_fp16)[name = tensor<string, []>("input_83_cast_fp16")];
            tensor<int32, [1]> hidden_states_31_axes_0 = const()[name = tensor<string, []>("hidden_states_31_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(121416192)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(121418816)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_31_cast_fp16 = layer_norm(axes = hidden_states_31_axes_0, beta = text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16, x = input_83_cast_fp16)[name = tensor<string, []>("hidden_states_31_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(121421440))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(122650304))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(122650496)))];
            tensor<fp16, [1, 77, 1280]> linear_30_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_31_cast_fp16)[name = tensor<string, []>("linear_30_cast_fp16")];
            tensor<fp16, []> var_583_to_fp16 = const()[name = tensor<string, []>("op_583_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_35_cast_fp16 = mul(x = linear_30_cast_fp16, y = var_583_to_fp16)[name = tensor<string, []>("tensor_35_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(122653120))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(123881984))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(123882176)))];
            tensor<fp16, [1, 77, 1280]> linear_31_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_31_cast_fp16)[name = tensor<string, []>("linear_31_cast_fp16")];
            tensor<int32, [4]> var_588 = const()[name = tensor<string, []>("op_588"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_589_cast_fp16 = reshape(shape = var_588, x = linear_31_cast_fp16)[name = tensor<string, []>("op_589_cast_fp16")];
            tensor<int32, [4]> var_590_perm_0 = const()[name = tensor<string, []>("op_590_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(123884800))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(125113664))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(125113856)))];
            tensor<fp16, [1, 77, 1280]> linear_32_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_31_cast_fp16)[name = tensor<string, []>("linear_32_cast_fp16")];
            tensor<int32, [4]> var_595 = const()[name = tensor<string, []>("op_595"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_596_cast_fp16 = reshape(shape = var_595, x = linear_32_cast_fp16)[name = tensor<string, []>("op_596_cast_fp16")];
            tensor<int32, [4]> var_597_perm_0 = const()[name = tensor<string, []>("op_597_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_604 = const()[name = tensor<string, []>("op_604"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_605_cast_fp16 = reshape(shape = var_604, x = tensor_35_cast_fp16)[name = tensor<string, []>("op_605_cast_fp16")];
            tensor<int32, [4]> var_606_perm_0 = const()[name = tensor<string, []>("op_606_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_608 = const()[name = tensor<string, []>("op_608"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_606_cast_fp16 = transpose(perm = var_606_perm_0, x = var_605_cast_fp16)[name = tensor<string, []>("transpose_107")];
            tensor<fp16, [20, 77, 64]> query_states_11_cast_fp16 = reshape(shape = var_608, x = var_606_cast_fp16)[name = tensor<string, []>("query_states_11_cast_fp16")];
            tensor<int32, [3]> var_610 = const()[name = tensor<string, []>("op_610"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_590_cast_fp16 = transpose(perm = var_590_perm_0, x = var_589_cast_fp16)[name = tensor<string, []>("transpose_106")];
            tensor<fp16, [20, 77, 64]> key_states_23_cast_fp16 = reshape(shape = var_610, x = var_590_cast_fp16)[name = tensor<string, []>("key_states_23_cast_fp16")];
            tensor<int32, [3]> var_612 = const()[name = tensor<string, []>("op_612"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_597_cast_fp16 = transpose(perm = var_597_perm_0, x = var_596_cast_fp16)[name = tensor<string, []>("transpose_105")];
            tensor<fp16, [20, 77, 64]> value_states_23_cast_fp16 = reshape(shape = var_612, x = var_597_cast_fp16)[name = tensor<string, []>("value_states_23_cast_fp16")];
            tensor<bool, []> attn_weights_31_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_31_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_31_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_31_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_31_cast_fp16 = matmul(transpose_x = attn_weights_31_transpose_x_1, transpose_y = attn_weights_31_transpose_y_1, x = query_states_11_cast_fp16, y = key_states_23_cast_fp16)[name = tensor<string, []>("attn_weights_31_cast_fp16")];
            tensor<int32, [4]> var_617 = const()[name = tensor<string, []>("op_617"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_618_cast_fp16 = reshape(shape = var_617, x = attn_weights_31_cast_fp16)[name = tensor<string, []>("op_618_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_33_cast_fp16 = add(x = var_618_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_33_cast_fp16")];
            tensor<int32, [3]> var_623 = const()[name = tensor<string, []>("op_623"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_85_cast_fp16 = reshape(shape = var_623, x = attn_weights_33_cast_fp16)[name = tensor<string, []>("input_85_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_87_cast_fp16 = softmax(axis = var_5, x = input_85_cast_fp16)[name = tensor<string, []>("input_87_cast_fp16")];
            tensor<bool, []> attn_output_31_transpose_x_0 = const()[name = tensor<string, []>("attn_output_31_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_31_transpose_y_0 = const()[name = tensor<string, []>("attn_output_31_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_31_cast_fp16 = matmul(transpose_x = attn_output_31_transpose_x_0, transpose_y = attn_output_31_transpose_y_0, x = input_87_cast_fp16, y = value_states_23_cast_fp16)[name = tensor<string, []>("attn_output_31_cast_fp16")];
            tensor<int32, [4]> var_628 = const()[name = tensor<string, []>("op_628"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_33_cast_fp16 = reshape(shape = var_628, x = attn_output_31_cast_fp16)[name = tensor<string, []>("attn_output_33_cast_fp16")];
            tensor<int32, [4]> attn_output_35_perm_0 = const()[name = tensor<string, []>("attn_output_35_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_631 = const()[name = tensor<string, []>("op_631"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_35_cast_fp16 = transpose(perm = attn_output_35_perm_0, x = attn_output_33_cast_fp16)[name = tensor<string, []>("transpose_104")];
            tensor<fp16, [1, 77, 1280]> input_89_cast_fp16 = reshape(shape = var_631, x = attn_output_35_cast_fp16)[name = tensor<string, []>("input_89_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(125116480))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126345344))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126345536)))];
            tensor<fp16, [1, 77, 1280]> linear_33_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized, x = input_89_cast_fp16)[name = tensor<string, []>("linear_33_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_91_cast_fp16 = add(x = input_83_cast_fp16, y = linear_33_cast_fp16)[name = tensor<string, []>("input_91_cast_fp16")];
            tensor<int32, [1]> input_93_axes_0 = const()[name = tensor<string, []>("input_93_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126348160)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126350784)))];
            tensor<fp16, [1, 77, 1280]> input_93_cast_fp16 = layer_norm(axes = input_93_axes_0, beta = text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16, x = input_91_cast_fp16)[name = tensor<string, []>("input_93_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126353408))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(131268672))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(131268864)))];
            tensor<fp16, [1, 77, 5120]> linear_34_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized, x = input_93_cast_fp16)[name = tensor<string, []>("linear_34_cast_fp16")];
            tensor<string, []> input_97_mode_0 = const()[name = tensor<string, []>("input_97_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_97_cast_fp16 = gelu(mode = input_97_mode_0, x = linear_34_cast_fp16)[name = tensor<string, []>("input_97_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(131279168))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136194432))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136194624)))];
            tensor<fp16, [1, 77, 1280]> linear_35_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized, x = input_97_cast_fp16)[name = tensor<string, []>("linear_35_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_99_cast_fp16 = add(x = input_91_cast_fp16, y = linear_35_cast_fp16)[name = tensor<string, []>("input_99_cast_fp16")];
            tensor<int32, [1]> hidden_states_37_axes_0 = const()[name = tensor<string, []>("hidden_states_37_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136197248)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136199872)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_37_cast_fp16 = layer_norm(axes = hidden_states_37_axes_0, beta = text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16, x = input_99_cast_fp16)[name = tensor<string, []>("hidden_states_37_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136202496))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(137431360))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(137431552)))];
            tensor<fp16, [1, 77, 1280]> linear_36_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_37_cast_fp16)[name = tensor<string, []>("linear_36_cast_fp16")];
            tensor<fp16, []> var_670_to_fp16 = const()[name = tensor<string, []>("op_670_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_41_cast_fp16 = mul(x = linear_36_cast_fp16, y = var_670_to_fp16)[name = tensor<string, []>("tensor_41_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(137434176))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(138663040))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(138663232)))];
            tensor<fp16, [1, 77, 1280]> linear_37_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_37_cast_fp16)[name = tensor<string, []>("linear_37_cast_fp16")];
            tensor<int32, [4]> var_675 = const()[name = tensor<string, []>("op_675"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_676_cast_fp16 = reshape(shape = var_675, x = linear_37_cast_fp16)[name = tensor<string, []>("op_676_cast_fp16")];
            tensor<int32, [4]> var_677_perm_0 = const()[name = tensor<string, []>("op_677_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(138665856))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139894720))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139894912)))];
            tensor<fp16, [1, 77, 1280]> linear_38_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_37_cast_fp16)[name = tensor<string, []>("linear_38_cast_fp16")];
            tensor<int32, [4]> var_682 = const()[name = tensor<string, []>("op_682"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_683_cast_fp16 = reshape(shape = var_682, x = linear_38_cast_fp16)[name = tensor<string, []>("op_683_cast_fp16")];
            tensor<int32, [4]> var_684_perm_0 = const()[name = tensor<string, []>("op_684_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_691 = const()[name = tensor<string, []>("op_691"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_692_cast_fp16 = reshape(shape = var_691, x = tensor_41_cast_fp16)[name = tensor<string, []>("op_692_cast_fp16")];
            tensor<int32, [4]> var_693_perm_0 = const()[name = tensor<string, []>("op_693_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_695 = const()[name = tensor<string, []>("op_695"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_693_cast_fp16 = transpose(perm = var_693_perm_0, x = var_692_cast_fp16)[name = tensor<string, []>("transpose_103")];
            tensor<fp16, [20, 77, 64]> query_states_13_cast_fp16 = reshape(shape = var_695, x = var_693_cast_fp16)[name = tensor<string, []>("query_states_13_cast_fp16")];
            tensor<int32, [3]> var_697 = const()[name = tensor<string, []>("op_697"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_677_cast_fp16 = transpose(perm = var_677_perm_0, x = var_676_cast_fp16)[name = tensor<string, []>("transpose_102")];
            tensor<fp16, [20, 77, 64]> key_states_27_cast_fp16 = reshape(shape = var_697, x = var_677_cast_fp16)[name = tensor<string, []>("key_states_27_cast_fp16")];
            tensor<int32, [3]> var_699 = const()[name = tensor<string, []>("op_699"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_684_cast_fp16 = transpose(perm = var_684_perm_0, x = var_683_cast_fp16)[name = tensor<string, []>("transpose_101")];
            tensor<fp16, [20, 77, 64]> value_states_27_cast_fp16 = reshape(shape = var_699, x = var_684_cast_fp16)[name = tensor<string, []>("value_states_27_cast_fp16")];
            tensor<bool, []> attn_weights_37_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_37_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_37_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_37_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_37_cast_fp16 = matmul(transpose_x = attn_weights_37_transpose_x_1, transpose_y = attn_weights_37_transpose_y_1, x = query_states_13_cast_fp16, y = key_states_27_cast_fp16)[name = tensor<string, []>("attn_weights_37_cast_fp16")];
            tensor<int32, [4]> var_704 = const()[name = tensor<string, []>("op_704"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_705_cast_fp16 = reshape(shape = var_704, x = attn_weights_37_cast_fp16)[name = tensor<string, []>("op_705_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_39_cast_fp16 = add(x = var_705_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_39_cast_fp16")];
            tensor<int32, [3]> var_710 = const()[name = tensor<string, []>("op_710"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_101_cast_fp16 = reshape(shape = var_710, x = attn_weights_39_cast_fp16)[name = tensor<string, []>("input_101_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_103_cast_fp16 = softmax(axis = var_5, x = input_101_cast_fp16)[name = tensor<string, []>("input_103_cast_fp16")];
            tensor<bool, []> attn_output_37_transpose_x_0 = const()[name = tensor<string, []>("attn_output_37_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_37_transpose_y_0 = const()[name = tensor<string, []>("attn_output_37_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_37_cast_fp16 = matmul(transpose_x = attn_output_37_transpose_x_0, transpose_y = attn_output_37_transpose_y_0, x = input_103_cast_fp16, y = value_states_27_cast_fp16)[name = tensor<string, []>("attn_output_37_cast_fp16")];
            tensor<int32, [4]> var_715 = const()[name = tensor<string, []>("op_715"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_39_cast_fp16 = reshape(shape = var_715, x = attn_output_37_cast_fp16)[name = tensor<string, []>("attn_output_39_cast_fp16")];
            tensor<int32, [4]> attn_output_41_perm_0 = const()[name = tensor<string, []>("attn_output_41_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_718 = const()[name = tensor<string, []>("op_718"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_41_cast_fp16 = transpose(perm = attn_output_41_perm_0, x = attn_output_39_cast_fp16)[name = tensor<string, []>("transpose_100")];
            tensor<fp16, [1, 77, 1280]> input_105_cast_fp16 = reshape(shape = var_718, x = attn_output_41_cast_fp16)[name = tensor<string, []>("input_105_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139897536))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141126400))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141126592)))];
            tensor<fp16, [1, 77, 1280]> linear_39_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized, x = input_105_cast_fp16)[name = tensor<string, []>("linear_39_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_107_cast_fp16 = add(x = input_99_cast_fp16, y = linear_39_cast_fp16)[name = tensor<string, []>("input_107_cast_fp16")];
            tensor<int32, [1]> input_109_axes_0 = const()[name = tensor<string, []>("input_109_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141129216)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141131840)))];
            tensor<fp16, [1, 77, 1280]> input_109_cast_fp16 = layer_norm(axes = input_109_axes_0, beta = text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16, x = input_107_cast_fp16)[name = tensor<string, []>("input_109_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141134464))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(146049728))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(146049920)))];
            tensor<fp16, [1, 77, 5120]> linear_40_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized, x = input_109_cast_fp16)[name = tensor<string, []>("linear_40_cast_fp16")];
            tensor<string, []> input_113_mode_0 = const()[name = tensor<string, []>("input_113_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_113_cast_fp16 = gelu(mode = input_113_mode_0, x = linear_40_cast_fp16)[name = tensor<string, []>("input_113_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(146060224))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(150975488))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(150975680)))];
            tensor<fp16, [1, 77, 1280]> linear_41_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized, x = input_113_cast_fp16)[name = tensor<string, []>("linear_41_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_115_cast_fp16 = add(x = input_107_cast_fp16, y = linear_41_cast_fp16)[name = tensor<string, []>("input_115_cast_fp16")];
            tensor<int32, [1]> hidden_states_43_axes_0 = const()[name = tensor<string, []>("hidden_states_43_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(150978304)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(150980928)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_43_cast_fp16 = layer_norm(axes = hidden_states_43_axes_0, beta = text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16, x = input_115_cast_fp16)[name = tensor<string, []>("hidden_states_43_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(150983552))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152212416))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152212608)))];
            tensor<fp16, [1, 77, 1280]> linear_42_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_43_cast_fp16)[name = tensor<string, []>("linear_42_cast_fp16")];
            tensor<fp16, []> var_757_to_fp16 = const()[name = tensor<string, []>("op_757_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_47_cast_fp16 = mul(x = linear_42_cast_fp16, y = var_757_to_fp16)[name = tensor<string, []>("tensor_47_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152215232))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(153444096))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(153444288)))];
            tensor<fp16, [1, 77, 1280]> linear_43_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_43_cast_fp16)[name = tensor<string, []>("linear_43_cast_fp16")];
            tensor<int32, [4]> var_762 = const()[name = tensor<string, []>("op_762"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_763_cast_fp16 = reshape(shape = var_762, x = linear_43_cast_fp16)[name = tensor<string, []>("op_763_cast_fp16")];
            tensor<int32, [4]> var_764_perm_0 = const()[name = tensor<string, []>("op_764_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(153446912))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(154675776))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(154675968)))];
            tensor<fp16, [1, 77, 1280]> linear_44_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_43_cast_fp16)[name = tensor<string, []>("linear_44_cast_fp16")];
            tensor<int32, [4]> var_769 = const()[name = tensor<string, []>("op_769"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_770_cast_fp16 = reshape(shape = var_769, x = linear_44_cast_fp16)[name = tensor<string, []>("op_770_cast_fp16")];
            tensor<int32, [4]> var_771_perm_0 = const()[name = tensor<string, []>("op_771_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_778 = const()[name = tensor<string, []>("op_778"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_779_cast_fp16 = reshape(shape = var_778, x = tensor_47_cast_fp16)[name = tensor<string, []>("op_779_cast_fp16")];
            tensor<int32, [4]> var_780_perm_0 = const()[name = tensor<string, []>("op_780_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_782 = const()[name = tensor<string, []>("op_782"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_780_cast_fp16 = transpose(perm = var_780_perm_0, x = var_779_cast_fp16)[name = tensor<string, []>("transpose_99")];
            tensor<fp16, [20, 77, 64]> query_states_15_cast_fp16 = reshape(shape = var_782, x = var_780_cast_fp16)[name = tensor<string, []>("query_states_15_cast_fp16")];
            tensor<int32, [3]> var_784 = const()[name = tensor<string, []>("op_784"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_764_cast_fp16 = transpose(perm = var_764_perm_0, x = var_763_cast_fp16)[name = tensor<string, []>("transpose_98")];
            tensor<fp16, [20, 77, 64]> key_states_31_cast_fp16 = reshape(shape = var_784, x = var_764_cast_fp16)[name = tensor<string, []>("key_states_31_cast_fp16")];
            tensor<int32, [3]> var_786 = const()[name = tensor<string, []>("op_786"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_771_cast_fp16 = transpose(perm = var_771_perm_0, x = var_770_cast_fp16)[name = tensor<string, []>("transpose_97")];
            tensor<fp16, [20, 77, 64]> value_states_31_cast_fp16 = reshape(shape = var_786, x = var_771_cast_fp16)[name = tensor<string, []>("value_states_31_cast_fp16")];
            tensor<bool, []> attn_weights_43_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_43_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_43_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_43_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_43_cast_fp16 = matmul(transpose_x = attn_weights_43_transpose_x_1, transpose_y = attn_weights_43_transpose_y_1, x = query_states_15_cast_fp16, y = key_states_31_cast_fp16)[name = tensor<string, []>("attn_weights_43_cast_fp16")];
            tensor<int32, [4]> var_791 = const()[name = tensor<string, []>("op_791"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_792_cast_fp16 = reshape(shape = var_791, x = attn_weights_43_cast_fp16)[name = tensor<string, []>("op_792_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_45_cast_fp16 = add(x = var_792_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_45_cast_fp16")];
            tensor<int32, [3]> var_797 = const()[name = tensor<string, []>("op_797"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_117_cast_fp16 = reshape(shape = var_797, x = attn_weights_45_cast_fp16)[name = tensor<string, []>("input_117_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_119_cast_fp16 = softmax(axis = var_5, x = input_117_cast_fp16)[name = tensor<string, []>("input_119_cast_fp16")];
            tensor<bool, []> attn_output_43_transpose_x_0 = const()[name = tensor<string, []>("attn_output_43_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_43_transpose_y_0 = const()[name = tensor<string, []>("attn_output_43_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_43_cast_fp16 = matmul(transpose_x = attn_output_43_transpose_x_0, transpose_y = attn_output_43_transpose_y_0, x = input_119_cast_fp16, y = value_states_31_cast_fp16)[name = tensor<string, []>("attn_output_43_cast_fp16")];
            tensor<int32, [4]> var_802 = const()[name = tensor<string, []>("op_802"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_45_cast_fp16 = reshape(shape = var_802, x = attn_output_43_cast_fp16)[name = tensor<string, []>("attn_output_45_cast_fp16")];
            tensor<int32, [4]> attn_output_47_perm_0 = const()[name = tensor<string, []>("attn_output_47_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_805 = const()[name = tensor<string, []>("op_805"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_47_cast_fp16 = transpose(perm = attn_output_47_perm_0, x = attn_output_45_cast_fp16)[name = tensor<string, []>("transpose_96")];
            tensor<fp16, [1, 77, 1280]> input_121_cast_fp16 = reshape(shape = var_805, x = attn_output_47_cast_fp16)[name = tensor<string, []>("input_121_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(154678592))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155907456))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155907648)))];
            tensor<fp16, [1, 77, 1280]> linear_45_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized, x = input_121_cast_fp16)[name = tensor<string, []>("linear_45_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_123_cast_fp16 = add(x = input_115_cast_fp16, y = linear_45_cast_fp16)[name = tensor<string, []>("input_123_cast_fp16")];
            tensor<int32, [1]> input_125_axes_0 = const()[name = tensor<string, []>("input_125_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155910272)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155912896)))];
            tensor<fp16, [1, 77, 1280]> input_125_cast_fp16 = layer_norm(axes = input_125_axes_0, beta = text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16, x = input_123_cast_fp16)[name = tensor<string, []>("input_125_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155915520))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(160830784))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(160830976)))];
            tensor<fp16, [1, 77, 5120]> linear_46_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized, x = input_125_cast_fp16)[name = tensor<string, []>("linear_46_cast_fp16")];
            tensor<string, []> input_129_mode_0 = const()[name = tensor<string, []>("input_129_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_129_cast_fp16 = gelu(mode = input_129_mode_0, x = linear_46_cast_fp16)[name = tensor<string, []>("input_129_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(160841280))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165756544))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165756736)))];
            tensor<fp16, [1, 77, 1280]> linear_47_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized, x = input_129_cast_fp16)[name = tensor<string, []>("linear_47_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_131_cast_fp16 = add(x = input_123_cast_fp16, y = linear_47_cast_fp16)[name = tensor<string, []>("input_131_cast_fp16")];
            tensor<int32, [1]> hidden_states_49_axes_0 = const()[name = tensor<string, []>("hidden_states_49_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165759360)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165761984)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_49_cast_fp16 = layer_norm(axes = hidden_states_49_axes_0, beta = text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16, x = input_131_cast_fp16)[name = tensor<string, []>("hidden_states_49_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165764608))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166993472))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166993664)))];
            tensor<fp16, [1, 77, 1280]> linear_48_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_49_cast_fp16)[name = tensor<string, []>("linear_48_cast_fp16")];
            tensor<fp16, []> var_844_to_fp16 = const()[name = tensor<string, []>("op_844_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_53_cast_fp16 = mul(x = linear_48_cast_fp16, y = var_844_to_fp16)[name = tensor<string, []>("tensor_53_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166996288))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(168225152))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(168225344)))];
            tensor<fp16, [1, 77, 1280]> linear_49_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_49_cast_fp16)[name = tensor<string, []>("linear_49_cast_fp16")];
            tensor<int32, [4]> var_849 = const()[name = tensor<string, []>("op_849"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_850_cast_fp16 = reshape(shape = var_849, x = linear_49_cast_fp16)[name = tensor<string, []>("op_850_cast_fp16")];
            tensor<int32, [4]> var_851_perm_0 = const()[name = tensor<string, []>("op_851_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(168227968))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(169456832))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(169457024)))];
            tensor<fp16, [1, 77, 1280]> linear_50_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_49_cast_fp16)[name = tensor<string, []>("linear_50_cast_fp16")];
            tensor<int32, [4]> var_856 = const()[name = tensor<string, []>("op_856"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_857_cast_fp16 = reshape(shape = var_856, x = linear_50_cast_fp16)[name = tensor<string, []>("op_857_cast_fp16")];
            tensor<int32, [4]> var_858_perm_0 = const()[name = tensor<string, []>("op_858_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_865 = const()[name = tensor<string, []>("op_865"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_866_cast_fp16 = reshape(shape = var_865, x = tensor_53_cast_fp16)[name = tensor<string, []>("op_866_cast_fp16")];
            tensor<int32, [4]> var_867_perm_0 = const()[name = tensor<string, []>("op_867_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_869 = const()[name = tensor<string, []>("op_869"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_867_cast_fp16 = transpose(perm = var_867_perm_0, x = var_866_cast_fp16)[name = tensor<string, []>("transpose_95")];
            tensor<fp16, [20, 77, 64]> query_states_17_cast_fp16 = reshape(shape = var_869, x = var_867_cast_fp16)[name = tensor<string, []>("query_states_17_cast_fp16")];
            tensor<int32, [3]> var_871 = const()[name = tensor<string, []>("op_871"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_851_cast_fp16 = transpose(perm = var_851_perm_0, x = var_850_cast_fp16)[name = tensor<string, []>("transpose_94")];
            tensor<fp16, [20, 77, 64]> key_states_35_cast_fp16 = reshape(shape = var_871, x = var_851_cast_fp16)[name = tensor<string, []>("key_states_35_cast_fp16")];
            tensor<int32, [3]> var_873 = const()[name = tensor<string, []>("op_873"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_858_cast_fp16 = transpose(perm = var_858_perm_0, x = var_857_cast_fp16)[name = tensor<string, []>("transpose_93")];
            tensor<fp16, [20, 77, 64]> value_states_35_cast_fp16 = reshape(shape = var_873, x = var_858_cast_fp16)[name = tensor<string, []>("value_states_35_cast_fp16")];
            tensor<bool, []> attn_weights_49_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_49_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_49_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_49_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_49_cast_fp16 = matmul(transpose_x = attn_weights_49_transpose_x_1, transpose_y = attn_weights_49_transpose_y_1, x = query_states_17_cast_fp16, y = key_states_35_cast_fp16)[name = tensor<string, []>("attn_weights_49_cast_fp16")];
            tensor<int32, [4]> var_878 = const()[name = tensor<string, []>("op_878"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_879_cast_fp16 = reshape(shape = var_878, x = attn_weights_49_cast_fp16)[name = tensor<string, []>("op_879_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_51_cast_fp16 = add(x = var_879_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_51_cast_fp16")];
            tensor<int32, [3]> var_884 = const()[name = tensor<string, []>("op_884"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_133_cast_fp16 = reshape(shape = var_884, x = attn_weights_51_cast_fp16)[name = tensor<string, []>("input_133_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_135_cast_fp16 = softmax(axis = var_5, x = input_133_cast_fp16)[name = tensor<string, []>("input_135_cast_fp16")];
            tensor<bool, []> attn_output_49_transpose_x_0 = const()[name = tensor<string, []>("attn_output_49_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_49_transpose_y_0 = const()[name = tensor<string, []>("attn_output_49_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_49_cast_fp16 = matmul(transpose_x = attn_output_49_transpose_x_0, transpose_y = attn_output_49_transpose_y_0, x = input_135_cast_fp16, y = value_states_35_cast_fp16)[name = tensor<string, []>("attn_output_49_cast_fp16")];
            tensor<int32, [4]> var_889 = const()[name = tensor<string, []>("op_889"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_51_cast_fp16 = reshape(shape = var_889, x = attn_output_49_cast_fp16)[name = tensor<string, []>("attn_output_51_cast_fp16")];
            tensor<int32, [4]> attn_output_53_perm_0 = const()[name = tensor<string, []>("attn_output_53_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_892 = const()[name = tensor<string, []>("op_892"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_53_cast_fp16 = transpose(perm = attn_output_53_perm_0, x = attn_output_51_cast_fp16)[name = tensor<string, []>("transpose_92")];
            tensor<fp16, [1, 77, 1280]> input_137_cast_fp16 = reshape(shape = var_892, x = attn_output_53_cast_fp16)[name = tensor<string, []>("input_137_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(169459648))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170688512))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170688704)))];
            tensor<fp16, [1, 77, 1280]> linear_51_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized, x = input_137_cast_fp16)[name = tensor<string, []>("linear_51_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_139_cast_fp16 = add(x = input_131_cast_fp16, y = linear_51_cast_fp16)[name = tensor<string, []>("input_139_cast_fp16")];
            tensor<int32, [1]> input_141_axes_0 = const()[name = tensor<string, []>("input_141_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170691328)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170693952)))];
            tensor<fp16, [1, 77, 1280]> input_141_cast_fp16 = layer_norm(axes = input_141_axes_0, beta = text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16, x = input_139_cast_fp16)[name = tensor<string, []>("input_141_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170696576))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(175611840))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(175612032)))];
            tensor<fp16, [1, 77, 5120]> linear_52_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized, x = input_141_cast_fp16)[name = tensor<string, []>("linear_52_cast_fp16")];
            tensor<string, []> input_145_mode_0 = const()[name = tensor<string, []>("input_145_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_145_cast_fp16 = gelu(mode = input_145_mode_0, x = linear_52_cast_fp16)[name = tensor<string, []>("input_145_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(175622336))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180537600))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180537792)))];
            tensor<fp16, [1, 77, 1280]> linear_53_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized, x = input_145_cast_fp16)[name = tensor<string, []>("linear_53_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_147_cast_fp16 = add(x = input_139_cast_fp16, y = linear_53_cast_fp16)[name = tensor<string, []>("input_147_cast_fp16")];
            tensor<int32, [1]> hidden_states_55_axes_0 = const()[name = tensor<string, []>("hidden_states_55_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180540416)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180543040)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_55_cast_fp16 = layer_norm(axes = hidden_states_55_axes_0, beta = text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16, x = input_147_cast_fp16)[name = tensor<string, []>("hidden_states_55_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180545664))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181774528))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181774720)))];
            tensor<fp16, [1, 77, 1280]> linear_54_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_55_cast_fp16)[name = tensor<string, []>("linear_54_cast_fp16")];
            tensor<fp16, []> var_931_to_fp16 = const()[name = tensor<string, []>("op_931_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_59_cast_fp16 = mul(x = linear_54_cast_fp16, y = var_931_to_fp16)[name = tensor<string, []>("tensor_59_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181777344))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(183006208))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(183006400)))];
            tensor<fp16, [1, 77, 1280]> linear_55_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_55_cast_fp16)[name = tensor<string, []>("linear_55_cast_fp16")];
            tensor<int32, [4]> var_936 = const()[name = tensor<string, []>("op_936"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_937_cast_fp16 = reshape(shape = var_936, x = linear_55_cast_fp16)[name = tensor<string, []>("op_937_cast_fp16")];
            tensor<int32, [4]> var_938_perm_0 = const()[name = tensor<string, []>("op_938_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(183009024))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(184237888))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(184238080)))];
            tensor<fp16, [1, 77, 1280]> linear_56_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_55_cast_fp16)[name = tensor<string, []>("linear_56_cast_fp16")];
            tensor<int32, [4]> var_943 = const()[name = tensor<string, []>("op_943"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_944_cast_fp16 = reshape(shape = var_943, x = linear_56_cast_fp16)[name = tensor<string, []>("op_944_cast_fp16")];
            tensor<int32, [4]> var_945_perm_0 = const()[name = tensor<string, []>("op_945_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_952 = const()[name = tensor<string, []>("op_952"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_953_cast_fp16 = reshape(shape = var_952, x = tensor_59_cast_fp16)[name = tensor<string, []>("op_953_cast_fp16")];
            tensor<int32, [4]> var_954_perm_0 = const()[name = tensor<string, []>("op_954_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_956 = const()[name = tensor<string, []>("op_956"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_954_cast_fp16 = transpose(perm = var_954_perm_0, x = var_953_cast_fp16)[name = tensor<string, []>("transpose_91")];
            tensor<fp16, [20, 77, 64]> query_states_19_cast_fp16 = reshape(shape = var_956, x = var_954_cast_fp16)[name = tensor<string, []>("query_states_19_cast_fp16")];
            tensor<int32, [3]> var_958 = const()[name = tensor<string, []>("op_958"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_938_cast_fp16 = transpose(perm = var_938_perm_0, x = var_937_cast_fp16)[name = tensor<string, []>("transpose_90")];
            tensor<fp16, [20, 77, 64]> key_states_39_cast_fp16 = reshape(shape = var_958, x = var_938_cast_fp16)[name = tensor<string, []>("key_states_39_cast_fp16")];
            tensor<int32, [3]> var_960 = const()[name = tensor<string, []>("op_960"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_945_cast_fp16 = transpose(perm = var_945_perm_0, x = var_944_cast_fp16)[name = tensor<string, []>("transpose_89")];
            tensor<fp16, [20, 77, 64]> value_states_39_cast_fp16 = reshape(shape = var_960, x = var_945_cast_fp16)[name = tensor<string, []>("value_states_39_cast_fp16")];
            tensor<bool, []> attn_weights_55_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_55_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_55_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_55_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_55_cast_fp16 = matmul(transpose_x = attn_weights_55_transpose_x_1, transpose_y = attn_weights_55_transpose_y_1, x = query_states_19_cast_fp16, y = key_states_39_cast_fp16)[name = tensor<string, []>("attn_weights_55_cast_fp16")];
            tensor<int32, [4]> var_965 = const()[name = tensor<string, []>("op_965"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_966_cast_fp16 = reshape(shape = var_965, x = attn_weights_55_cast_fp16)[name = tensor<string, []>("op_966_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_57_cast_fp16 = add(x = var_966_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_57_cast_fp16")];
            tensor<int32, [3]> var_971 = const()[name = tensor<string, []>("op_971"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_149_cast_fp16 = reshape(shape = var_971, x = attn_weights_57_cast_fp16)[name = tensor<string, []>("input_149_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_151_cast_fp16 = softmax(axis = var_5, x = input_149_cast_fp16)[name = tensor<string, []>("input_151_cast_fp16")];
            tensor<bool, []> attn_output_55_transpose_x_0 = const()[name = tensor<string, []>("attn_output_55_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_55_transpose_y_0 = const()[name = tensor<string, []>("attn_output_55_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_55_cast_fp16 = matmul(transpose_x = attn_output_55_transpose_x_0, transpose_y = attn_output_55_transpose_y_0, x = input_151_cast_fp16, y = value_states_39_cast_fp16)[name = tensor<string, []>("attn_output_55_cast_fp16")];
            tensor<int32, [4]> var_976 = const()[name = tensor<string, []>("op_976"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_57_cast_fp16 = reshape(shape = var_976, x = attn_output_55_cast_fp16)[name = tensor<string, []>("attn_output_57_cast_fp16")];
            tensor<int32, [4]> attn_output_59_perm_0 = const()[name = tensor<string, []>("attn_output_59_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_979 = const()[name = tensor<string, []>("op_979"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_59_cast_fp16 = transpose(perm = attn_output_59_perm_0, x = attn_output_57_cast_fp16)[name = tensor<string, []>("transpose_88")];
            tensor<fp16, [1, 77, 1280]> input_153_cast_fp16 = reshape(shape = var_979, x = attn_output_59_cast_fp16)[name = tensor<string, []>("input_153_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(184240704))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(185469568))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(185469760)))];
            tensor<fp16, [1, 77, 1280]> linear_57_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized, x = input_153_cast_fp16)[name = tensor<string, []>("linear_57_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_155_cast_fp16 = add(x = input_147_cast_fp16, y = linear_57_cast_fp16)[name = tensor<string, []>("input_155_cast_fp16")];
            tensor<int32, [1]> input_157_axes_0 = const()[name = tensor<string, []>("input_157_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(185472384)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(185475008)))];
            tensor<fp16, [1, 77, 1280]> input_157_cast_fp16 = layer_norm(axes = input_157_axes_0, beta = text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16, x = input_155_cast_fp16)[name = tensor<string, []>("input_157_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(185477632))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(190392896))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(190393088)))];
            tensor<fp16, [1, 77, 5120]> linear_58_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized, x = input_157_cast_fp16)[name = tensor<string, []>("linear_58_cast_fp16")];
            tensor<string, []> input_161_mode_0 = const()[name = tensor<string, []>("input_161_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_161_cast_fp16 = gelu(mode = input_161_mode_0, x = linear_58_cast_fp16)[name = tensor<string, []>("input_161_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(190403392))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(195318656))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(195318848)))];
            tensor<fp16, [1, 77, 1280]> linear_59_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized, x = input_161_cast_fp16)[name = tensor<string, []>("linear_59_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_163_cast_fp16 = add(x = input_155_cast_fp16, y = linear_59_cast_fp16)[name = tensor<string, []>("input_163_cast_fp16")];
            tensor<int32, [1]> hidden_states_61_axes_0 = const()[name = tensor<string, []>("hidden_states_61_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(195321472)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(195324096)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_61_cast_fp16 = layer_norm(axes = hidden_states_61_axes_0, beta = text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16, x = input_163_cast_fp16)[name = tensor<string, []>("hidden_states_61_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(195326720))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(196555584))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(196555776)))];
            tensor<fp16, [1, 77, 1280]> linear_60_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_61_cast_fp16)[name = tensor<string, []>("linear_60_cast_fp16")];
            tensor<fp16, []> var_1018_to_fp16 = const()[name = tensor<string, []>("op_1018_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_65_cast_fp16 = mul(x = linear_60_cast_fp16, y = var_1018_to_fp16)[name = tensor<string, []>("tensor_65_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(196558400))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(197787264))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(197787456)))];
            tensor<fp16, [1, 77, 1280]> linear_61_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_61_cast_fp16)[name = tensor<string, []>("linear_61_cast_fp16")];
            tensor<int32, [4]> var_1023 = const()[name = tensor<string, []>("op_1023"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1024_cast_fp16 = reshape(shape = var_1023, x = linear_61_cast_fp16)[name = tensor<string, []>("op_1024_cast_fp16")];
            tensor<int32, [4]> var_1025_perm_0 = const()[name = tensor<string, []>("op_1025_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(197790080))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(199018944))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(199019136)))];
            tensor<fp16, [1, 77, 1280]> linear_62_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_61_cast_fp16)[name = tensor<string, []>("linear_62_cast_fp16")];
            tensor<int32, [4]> var_1030 = const()[name = tensor<string, []>("op_1030"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1031_cast_fp16 = reshape(shape = var_1030, x = linear_62_cast_fp16)[name = tensor<string, []>("op_1031_cast_fp16")];
            tensor<int32, [4]> var_1032_perm_0 = const()[name = tensor<string, []>("op_1032_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1039 = const()[name = tensor<string, []>("op_1039"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1040_cast_fp16 = reshape(shape = var_1039, x = tensor_65_cast_fp16)[name = tensor<string, []>("op_1040_cast_fp16")];
            tensor<int32, [4]> var_1041_perm_0 = const()[name = tensor<string, []>("op_1041_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1043 = const()[name = tensor<string, []>("op_1043"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1041_cast_fp16 = transpose(perm = var_1041_perm_0, x = var_1040_cast_fp16)[name = tensor<string, []>("transpose_87")];
            tensor<fp16, [20, 77, 64]> query_states_21_cast_fp16 = reshape(shape = var_1043, x = var_1041_cast_fp16)[name = tensor<string, []>("query_states_21_cast_fp16")];
            tensor<int32, [3]> var_1045 = const()[name = tensor<string, []>("op_1045"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1025_cast_fp16 = transpose(perm = var_1025_perm_0, x = var_1024_cast_fp16)[name = tensor<string, []>("transpose_86")];
            tensor<fp16, [20, 77, 64]> key_states_43_cast_fp16 = reshape(shape = var_1045, x = var_1025_cast_fp16)[name = tensor<string, []>("key_states_43_cast_fp16")];
            tensor<int32, [3]> var_1047 = const()[name = tensor<string, []>("op_1047"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1032_cast_fp16 = transpose(perm = var_1032_perm_0, x = var_1031_cast_fp16)[name = tensor<string, []>("transpose_85")];
            tensor<fp16, [20, 77, 64]> value_states_43_cast_fp16 = reshape(shape = var_1047, x = var_1032_cast_fp16)[name = tensor<string, []>("value_states_43_cast_fp16")];
            tensor<bool, []> attn_weights_61_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_61_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_61_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_61_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_61_cast_fp16 = matmul(transpose_x = attn_weights_61_transpose_x_1, transpose_y = attn_weights_61_transpose_y_1, x = query_states_21_cast_fp16, y = key_states_43_cast_fp16)[name = tensor<string, []>("attn_weights_61_cast_fp16")];
            tensor<int32, [4]> var_1052 = const()[name = tensor<string, []>("op_1052"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1053_cast_fp16 = reshape(shape = var_1052, x = attn_weights_61_cast_fp16)[name = tensor<string, []>("op_1053_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_63_cast_fp16 = add(x = var_1053_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_63_cast_fp16")];
            tensor<int32, [3]> var_1058 = const()[name = tensor<string, []>("op_1058"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_165_cast_fp16 = reshape(shape = var_1058, x = attn_weights_63_cast_fp16)[name = tensor<string, []>("input_165_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_167_cast_fp16 = softmax(axis = var_5, x = input_165_cast_fp16)[name = tensor<string, []>("input_167_cast_fp16")];
            tensor<bool, []> attn_output_61_transpose_x_0 = const()[name = tensor<string, []>("attn_output_61_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_61_transpose_y_0 = const()[name = tensor<string, []>("attn_output_61_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_61_cast_fp16 = matmul(transpose_x = attn_output_61_transpose_x_0, transpose_y = attn_output_61_transpose_y_0, x = input_167_cast_fp16, y = value_states_43_cast_fp16)[name = tensor<string, []>("attn_output_61_cast_fp16")];
            tensor<int32, [4]> var_1063 = const()[name = tensor<string, []>("op_1063"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_63_cast_fp16 = reshape(shape = var_1063, x = attn_output_61_cast_fp16)[name = tensor<string, []>("attn_output_63_cast_fp16")];
            tensor<int32, [4]> attn_output_65_perm_0 = const()[name = tensor<string, []>("attn_output_65_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1066 = const()[name = tensor<string, []>("op_1066"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_65_cast_fp16 = transpose(perm = attn_output_65_perm_0, x = attn_output_63_cast_fp16)[name = tensor<string, []>("transpose_84")];
            tensor<fp16, [1, 77, 1280]> input_169_cast_fp16 = reshape(shape = var_1066, x = attn_output_65_cast_fp16)[name = tensor<string, []>("input_169_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(199021760))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(200250624))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(200250816)))];
            tensor<fp16, [1, 77, 1280]> linear_63_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized, x = input_169_cast_fp16)[name = tensor<string, []>("linear_63_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_171_cast_fp16 = add(x = input_163_cast_fp16, y = linear_63_cast_fp16)[name = tensor<string, []>("input_171_cast_fp16")];
            tensor<int32, [1]> input_173_axes_0 = const()[name = tensor<string, []>("input_173_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(200253440)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(200256064)))];
            tensor<fp16, [1, 77, 1280]> input_173_cast_fp16 = layer_norm(axes = input_173_axes_0, beta = text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16, x = input_171_cast_fp16)[name = tensor<string, []>("input_173_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(200258688))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205173952))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205174144)))];
            tensor<fp16, [1, 77, 5120]> linear_64_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized, x = input_173_cast_fp16)[name = tensor<string, []>("linear_64_cast_fp16")];
            tensor<string, []> input_177_mode_0 = const()[name = tensor<string, []>("input_177_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_177_cast_fp16 = gelu(mode = input_177_mode_0, x = linear_64_cast_fp16)[name = tensor<string, []>("input_177_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205184448))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(210099712))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(210099904)))];
            tensor<fp16, [1, 77, 1280]> linear_65_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized, x = input_177_cast_fp16)[name = tensor<string, []>("linear_65_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_179_cast_fp16 = add(x = input_171_cast_fp16, y = linear_65_cast_fp16)[name = tensor<string, []>("input_179_cast_fp16")];
            tensor<int32, [1]> hidden_states_67_axes_0 = const()[name = tensor<string, []>("hidden_states_67_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(210102528)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(210105152)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_67_cast_fp16 = layer_norm(axes = hidden_states_67_axes_0, beta = text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16, x = input_179_cast_fp16)[name = tensor<string, []>("hidden_states_67_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(210107776))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211336640))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211336832)))];
            tensor<fp16, [1, 77, 1280]> linear_66_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_67_cast_fp16)[name = tensor<string, []>("linear_66_cast_fp16")];
            tensor<fp16, []> var_1105_to_fp16 = const()[name = tensor<string, []>("op_1105_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_71_cast_fp16 = mul(x = linear_66_cast_fp16, y = var_1105_to_fp16)[name = tensor<string, []>("tensor_71_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211339456))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(212568320))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(212568512)))];
            tensor<fp16, [1, 77, 1280]> linear_67_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_67_cast_fp16)[name = tensor<string, []>("linear_67_cast_fp16")];
            tensor<int32, [4]> var_1110 = const()[name = tensor<string, []>("op_1110"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1111_cast_fp16 = reshape(shape = var_1110, x = linear_67_cast_fp16)[name = tensor<string, []>("op_1111_cast_fp16")];
            tensor<int32, [4]> var_1112_perm_0 = const()[name = tensor<string, []>("op_1112_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(212571136))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(213800000))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(213800192)))];
            tensor<fp16, [1, 77, 1280]> linear_68_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_67_cast_fp16)[name = tensor<string, []>("linear_68_cast_fp16")];
            tensor<int32, [4]> var_1117 = const()[name = tensor<string, []>("op_1117"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1118_cast_fp16 = reshape(shape = var_1117, x = linear_68_cast_fp16)[name = tensor<string, []>("op_1118_cast_fp16")];
            tensor<int32, [4]> var_1119_perm_0 = const()[name = tensor<string, []>("op_1119_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1126 = const()[name = tensor<string, []>("op_1126"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1127_cast_fp16 = reshape(shape = var_1126, x = tensor_71_cast_fp16)[name = tensor<string, []>("op_1127_cast_fp16")];
            tensor<int32, [4]> var_1128_perm_0 = const()[name = tensor<string, []>("op_1128_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1130 = const()[name = tensor<string, []>("op_1130"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1128_cast_fp16 = transpose(perm = var_1128_perm_0, x = var_1127_cast_fp16)[name = tensor<string, []>("transpose_83")];
            tensor<fp16, [20, 77, 64]> query_states_23_cast_fp16 = reshape(shape = var_1130, x = var_1128_cast_fp16)[name = tensor<string, []>("query_states_23_cast_fp16")];
            tensor<int32, [3]> var_1132 = const()[name = tensor<string, []>("op_1132"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1112_cast_fp16 = transpose(perm = var_1112_perm_0, x = var_1111_cast_fp16)[name = tensor<string, []>("transpose_82")];
            tensor<fp16, [20, 77, 64]> key_states_47_cast_fp16 = reshape(shape = var_1132, x = var_1112_cast_fp16)[name = tensor<string, []>("key_states_47_cast_fp16")];
            tensor<int32, [3]> var_1134 = const()[name = tensor<string, []>("op_1134"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1119_cast_fp16 = transpose(perm = var_1119_perm_0, x = var_1118_cast_fp16)[name = tensor<string, []>("transpose_81")];
            tensor<fp16, [20, 77, 64]> value_states_47_cast_fp16 = reshape(shape = var_1134, x = var_1119_cast_fp16)[name = tensor<string, []>("value_states_47_cast_fp16")];
            tensor<bool, []> attn_weights_67_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_67_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_67_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_67_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_67_cast_fp16 = matmul(transpose_x = attn_weights_67_transpose_x_1, transpose_y = attn_weights_67_transpose_y_1, x = query_states_23_cast_fp16, y = key_states_47_cast_fp16)[name = tensor<string, []>("attn_weights_67_cast_fp16")];
            tensor<int32, [4]> var_1139 = const()[name = tensor<string, []>("op_1139"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1140_cast_fp16 = reshape(shape = var_1139, x = attn_weights_67_cast_fp16)[name = tensor<string, []>("op_1140_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_69_cast_fp16 = add(x = var_1140_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_69_cast_fp16")];
            tensor<int32, [3]> var_1145 = const()[name = tensor<string, []>("op_1145"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_181_cast_fp16 = reshape(shape = var_1145, x = attn_weights_69_cast_fp16)[name = tensor<string, []>("input_181_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_183_cast_fp16 = softmax(axis = var_5, x = input_181_cast_fp16)[name = tensor<string, []>("input_183_cast_fp16")];
            tensor<bool, []> attn_output_67_transpose_x_0 = const()[name = tensor<string, []>("attn_output_67_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_67_transpose_y_0 = const()[name = tensor<string, []>("attn_output_67_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_67_cast_fp16 = matmul(transpose_x = attn_output_67_transpose_x_0, transpose_y = attn_output_67_transpose_y_0, x = input_183_cast_fp16, y = value_states_47_cast_fp16)[name = tensor<string, []>("attn_output_67_cast_fp16")];
            tensor<int32, [4]> var_1150 = const()[name = tensor<string, []>("op_1150"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_69_cast_fp16 = reshape(shape = var_1150, x = attn_output_67_cast_fp16)[name = tensor<string, []>("attn_output_69_cast_fp16")];
            tensor<int32, [4]> attn_output_71_perm_0 = const()[name = tensor<string, []>("attn_output_71_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1153 = const()[name = tensor<string, []>("op_1153"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_71_cast_fp16 = transpose(perm = attn_output_71_perm_0, x = attn_output_69_cast_fp16)[name = tensor<string, []>("transpose_80")];
            tensor<fp16, [1, 77, 1280]> input_185_cast_fp16 = reshape(shape = var_1153, x = attn_output_71_cast_fp16)[name = tensor<string, []>("input_185_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(213802816))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215031680))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215031872)))];
            tensor<fp16, [1, 77, 1280]> linear_69_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized, x = input_185_cast_fp16)[name = tensor<string, []>("linear_69_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_187_cast_fp16 = add(x = input_179_cast_fp16, y = linear_69_cast_fp16)[name = tensor<string, []>("input_187_cast_fp16")];
            tensor<int32, [1]> input_189_axes_0 = const()[name = tensor<string, []>("input_189_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215034496)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215037120)))];
            tensor<fp16, [1, 77, 1280]> input_189_cast_fp16 = layer_norm(axes = input_189_axes_0, beta = text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16, x = input_187_cast_fp16)[name = tensor<string, []>("input_189_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215039744))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(219955008))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(219955200)))];
            tensor<fp16, [1, 77, 5120]> linear_70_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized, x = input_189_cast_fp16)[name = tensor<string, []>("linear_70_cast_fp16")];
            tensor<string, []> input_193_mode_0 = const()[name = tensor<string, []>("input_193_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_193_cast_fp16 = gelu(mode = input_193_mode_0, x = linear_70_cast_fp16)[name = tensor<string, []>("input_193_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(219965504))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(224880768))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(224880960)))];
            tensor<fp16, [1, 77, 1280]> linear_71_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized, x = input_193_cast_fp16)[name = tensor<string, []>("linear_71_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_195_cast_fp16 = add(x = input_187_cast_fp16, y = linear_71_cast_fp16)[name = tensor<string, []>("input_195_cast_fp16")];
            tensor<int32, [1]> hidden_states_73_axes_0 = const()[name = tensor<string, []>("hidden_states_73_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(224883584)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(224886208)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_73_cast_fp16 = layer_norm(axes = hidden_states_73_axes_0, beta = text_encoder_text_model_encoder_layers_12_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_12_layer_norm1_weight_to_fp16, x = input_195_cast_fp16)[name = tensor<string, []>("hidden_states_73_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(224888832))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(226117696))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(226117888)))];
            tensor<fp16, [1, 77, 1280]> linear_72_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_73_cast_fp16)[name = tensor<string, []>("linear_72_cast_fp16")];
            tensor<fp16, []> var_1192_to_fp16 = const()[name = tensor<string, []>("op_1192_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_77_cast_fp16 = mul(x = linear_72_cast_fp16, y = var_1192_to_fp16)[name = tensor<string, []>("tensor_77_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(226120512))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(227349376))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(227349568)))];
            tensor<fp16, [1, 77, 1280]> linear_73_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_73_cast_fp16)[name = tensor<string, []>("linear_73_cast_fp16")];
            tensor<int32, [4]> var_1197 = const()[name = tensor<string, []>("op_1197"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1198_cast_fp16 = reshape(shape = var_1197, x = linear_73_cast_fp16)[name = tensor<string, []>("op_1198_cast_fp16")];
            tensor<int32, [4]> var_1199_perm_0 = const()[name = tensor<string, []>("op_1199_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(227352192))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(228581056))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(228581248)))];
            tensor<fp16, [1, 77, 1280]> linear_74_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_73_cast_fp16)[name = tensor<string, []>("linear_74_cast_fp16")];
            tensor<int32, [4]> var_1204 = const()[name = tensor<string, []>("op_1204"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1205_cast_fp16 = reshape(shape = var_1204, x = linear_74_cast_fp16)[name = tensor<string, []>("op_1205_cast_fp16")];
            tensor<int32, [4]> var_1206_perm_0 = const()[name = tensor<string, []>("op_1206_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1213 = const()[name = tensor<string, []>("op_1213"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1214_cast_fp16 = reshape(shape = var_1213, x = tensor_77_cast_fp16)[name = tensor<string, []>("op_1214_cast_fp16")];
            tensor<int32, [4]> var_1215_perm_0 = const()[name = tensor<string, []>("op_1215_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1217 = const()[name = tensor<string, []>("op_1217"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1215_cast_fp16 = transpose(perm = var_1215_perm_0, x = var_1214_cast_fp16)[name = tensor<string, []>("transpose_79")];
            tensor<fp16, [20, 77, 64]> query_states_25_cast_fp16 = reshape(shape = var_1217, x = var_1215_cast_fp16)[name = tensor<string, []>("query_states_25_cast_fp16")];
            tensor<int32, [3]> var_1219 = const()[name = tensor<string, []>("op_1219"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1199_cast_fp16 = transpose(perm = var_1199_perm_0, x = var_1198_cast_fp16)[name = tensor<string, []>("transpose_78")];
            tensor<fp16, [20, 77, 64]> key_states_51_cast_fp16 = reshape(shape = var_1219, x = var_1199_cast_fp16)[name = tensor<string, []>("key_states_51_cast_fp16")];
            tensor<int32, [3]> var_1221 = const()[name = tensor<string, []>("op_1221"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1206_cast_fp16 = transpose(perm = var_1206_perm_0, x = var_1205_cast_fp16)[name = tensor<string, []>("transpose_77")];
            tensor<fp16, [20, 77, 64]> value_states_51_cast_fp16 = reshape(shape = var_1221, x = var_1206_cast_fp16)[name = tensor<string, []>("value_states_51_cast_fp16")];
            tensor<bool, []> attn_weights_73_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_73_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_73_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_73_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_73_cast_fp16 = matmul(transpose_x = attn_weights_73_transpose_x_1, transpose_y = attn_weights_73_transpose_y_1, x = query_states_25_cast_fp16, y = key_states_51_cast_fp16)[name = tensor<string, []>("attn_weights_73_cast_fp16")];
            tensor<int32, [4]> var_1226 = const()[name = tensor<string, []>("op_1226"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1227_cast_fp16 = reshape(shape = var_1226, x = attn_weights_73_cast_fp16)[name = tensor<string, []>("op_1227_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_75_cast_fp16 = add(x = var_1227_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_75_cast_fp16")];
            tensor<int32, [3]> var_1232 = const()[name = tensor<string, []>("op_1232"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_197_cast_fp16 = reshape(shape = var_1232, x = attn_weights_75_cast_fp16)[name = tensor<string, []>("input_197_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_199_cast_fp16 = softmax(axis = var_5, x = input_197_cast_fp16)[name = tensor<string, []>("input_199_cast_fp16")];
            tensor<bool, []> attn_output_73_transpose_x_0 = const()[name = tensor<string, []>("attn_output_73_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_73_transpose_y_0 = const()[name = tensor<string, []>("attn_output_73_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_73_cast_fp16 = matmul(transpose_x = attn_output_73_transpose_x_0, transpose_y = attn_output_73_transpose_y_0, x = input_199_cast_fp16, y = value_states_51_cast_fp16)[name = tensor<string, []>("attn_output_73_cast_fp16")];
            tensor<int32, [4]> var_1237 = const()[name = tensor<string, []>("op_1237"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_75_cast_fp16 = reshape(shape = var_1237, x = attn_output_73_cast_fp16)[name = tensor<string, []>("attn_output_75_cast_fp16")];
            tensor<int32, [4]> attn_output_77_perm_0 = const()[name = tensor<string, []>("attn_output_77_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1240 = const()[name = tensor<string, []>("op_1240"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_77_cast_fp16 = transpose(perm = attn_output_77_perm_0, x = attn_output_75_cast_fp16)[name = tensor<string, []>("transpose_76")];
            tensor<fp16, [1, 77, 1280]> input_201_cast_fp16 = reshape(shape = var_1240, x = attn_output_77_cast_fp16)[name = tensor<string, []>("input_201_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(228583872))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(229812736))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(229812928)))];
            tensor<fp16, [1, 77, 1280]> linear_75_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16_palettized, x = input_201_cast_fp16)[name = tensor<string, []>("linear_75_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_203_cast_fp16 = add(x = input_195_cast_fp16, y = linear_75_cast_fp16)[name = tensor<string, []>("input_203_cast_fp16")];
            tensor<int32, [1]> input_205_axes_0 = const()[name = tensor<string, []>("input_205_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(229815552)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(229818176)))];
            tensor<fp16, [1, 77, 1280]> input_205_cast_fp16 = layer_norm(axes = input_205_axes_0, beta = text_encoder_text_model_encoder_layers_12_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_12_layer_norm2_weight_to_fp16, x = input_203_cast_fp16)[name = tensor<string, []>("input_205_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(229820800))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(234736064))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_12_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(234736256)))];
            tensor<fp16, [1, 77, 5120]> linear_76_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_12_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16_palettized, x = input_205_cast_fp16)[name = tensor<string, []>("linear_76_cast_fp16")];
            tensor<string, []> input_209_mode_0 = const()[name = tensor<string, []>("input_209_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_209_cast_fp16 = gelu(mode = input_209_mode_0, x = linear_76_cast_fp16)[name = tensor<string, []>("input_209_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_12_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(234746560))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(239661824))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(239662016)))];
            tensor<fp16, [1, 77, 1280]> linear_77_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_12_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_mlp_fc2_weight_to_fp16_palettized, x = input_209_cast_fp16)[name = tensor<string, []>("linear_77_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_211_cast_fp16 = add(x = input_203_cast_fp16, y = linear_77_cast_fp16)[name = tensor<string, []>("input_211_cast_fp16")];
            tensor<int32, [1]> hidden_states_79_axes_0 = const()[name = tensor<string, []>("hidden_states_79_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(239664640)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(239667264)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_79_cast_fp16 = layer_norm(axes = hidden_states_79_axes_0, beta = text_encoder_text_model_encoder_layers_13_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_13_layer_norm1_weight_to_fp16, x = input_211_cast_fp16)[name = tensor<string, []>("hidden_states_79_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(239669888))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(240898752))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(240898944)))];
            tensor<fp16, [1, 77, 1280]> linear_78_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_79_cast_fp16)[name = tensor<string, []>("linear_78_cast_fp16")];
            tensor<fp16, []> var_1279_to_fp16 = const()[name = tensor<string, []>("op_1279_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_83_cast_fp16 = mul(x = linear_78_cast_fp16, y = var_1279_to_fp16)[name = tensor<string, []>("tensor_83_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(240901568))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(242130432))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(242130624)))];
            tensor<fp16, [1, 77, 1280]> linear_79_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_79_cast_fp16)[name = tensor<string, []>("linear_79_cast_fp16")];
            tensor<int32, [4]> var_1284 = const()[name = tensor<string, []>("op_1284"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1285_cast_fp16 = reshape(shape = var_1284, x = linear_79_cast_fp16)[name = tensor<string, []>("op_1285_cast_fp16")];
            tensor<int32, [4]> var_1286_perm_0 = const()[name = tensor<string, []>("op_1286_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(242133248))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(243362112))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(243362304)))];
            tensor<fp16, [1, 77, 1280]> linear_80_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_79_cast_fp16)[name = tensor<string, []>("linear_80_cast_fp16")];
            tensor<int32, [4]> var_1291 = const()[name = tensor<string, []>("op_1291"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1292_cast_fp16 = reshape(shape = var_1291, x = linear_80_cast_fp16)[name = tensor<string, []>("op_1292_cast_fp16")];
            tensor<int32, [4]> var_1293_perm_0 = const()[name = tensor<string, []>("op_1293_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1300 = const()[name = tensor<string, []>("op_1300"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1301_cast_fp16 = reshape(shape = var_1300, x = tensor_83_cast_fp16)[name = tensor<string, []>("op_1301_cast_fp16")];
            tensor<int32, [4]> var_1302_perm_0 = const()[name = tensor<string, []>("op_1302_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1304 = const()[name = tensor<string, []>("op_1304"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1302_cast_fp16 = transpose(perm = var_1302_perm_0, x = var_1301_cast_fp16)[name = tensor<string, []>("transpose_75")];
            tensor<fp16, [20, 77, 64]> query_states_27_cast_fp16 = reshape(shape = var_1304, x = var_1302_cast_fp16)[name = tensor<string, []>("query_states_27_cast_fp16")];
            tensor<int32, [3]> var_1306 = const()[name = tensor<string, []>("op_1306"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1286_cast_fp16 = transpose(perm = var_1286_perm_0, x = var_1285_cast_fp16)[name = tensor<string, []>("transpose_74")];
            tensor<fp16, [20, 77, 64]> key_states_55_cast_fp16 = reshape(shape = var_1306, x = var_1286_cast_fp16)[name = tensor<string, []>("key_states_55_cast_fp16")];
            tensor<int32, [3]> var_1308 = const()[name = tensor<string, []>("op_1308"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1293_cast_fp16 = transpose(perm = var_1293_perm_0, x = var_1292_cast_fp16)[name = tensor<string, []>("transpose_73")];
            tensor<fp16, [20, 77, 64]> value_states_55_cast_fp16 = reshape(shape = var_1308, x = var_1293_cast_fp16)[name = tensor<string, []>("value_states_55_cast_fp16")];
            tensor<bool, []> attn_weights_79_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_79_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_79_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_79_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_79_cast_fp16 = matmul(transpose_x = attn_weights_79_transpose_x_1, transpose_y = attn_weights_79_transpose_y_1, x = query_states_27_cast_fp16, y = key_states_55_cast_fp16)[name = tensor<string, []>("attn_weights_79_cast_fp16")];
            tensor<int32, [4]> var_1313 = const()[name = tensor<string, []>("op_1313"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1314_cast_fp16 = reshape(shape = var_1313, x = attn_weights_79_cast_fp16)[name = tensor<string, []>("op_1314_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_81_cast_fp16 = add(x = var_1314_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_81_cast_fp16")];
            tensor<int32, [3]> var_1319 = const()[name = tensor<string, []>("op_1319"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_213_cast_fp16 = reshape(shape = var_1319, x = attn_weights_81_cast_fp16)[name = tensor<string, []>("input_213_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_215_cast_fp16 = softmax(axis = var_5, x = input_213_cast_fp16)[name = tensor<string, []>("input_215_cast_fp16")];
            tensor<bool, []> attn_output_79_transpose_x_0 = const()[name = tensor<string, []>("attn_output_79_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_79_transpose_y_0 = const()[name = tensor<string, []>("attn_output_79_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_79_cast_fp16 = matmul(transpose_x = attn_output_79_transpose_x_0, transpose_y = attn_output_79_transpose_y_0, x = input_215_cast_fp16, y = value_states_55_cast_fp16)[name = tensor<string, []>("attn_output_79_cast_fp16")];
            tensor<int32, [4]> var_1324 = const()[name = tensor<string, []>("op_1324"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_81_cast_fp16 = reshape(shape = var_1324, x = attn_output_79_cast_fp16)[name = tensor<string, []>("attn_output_81_cast_fp16")];
            tensor<int32, [4]> attn_output_83_perm_0 = const()[name = tensor<string, []>("attn_output_83_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1327 = const()[name = tensor<string, []>("op_1327"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_83_cast_fp16 = transpose(perm = attn_output_83_perm_0, x = attn_output_81_cast_fp16)[name = tensor<string, []>("transpose_72")];
            tensor<fp16, [1, 77, 1280]> input_217_cast_fp16 = reshape(shape = var_1327, x = attn_output_83_cast_fp16)[name = tensor<string, []>("input_217_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(243364928))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244593792))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244593984)))];
            tensor<fp16, [1, 77, 1280]> linear_81_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16_palettized, x = input_217_cast_fp16)[name = tensor<string, []>("linear_81_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_219_cast_fp16 = add(x = input_211_cast_fp16, y = linear_81_cast_fp16)[name = tensor<string, []>("input_219_cast_fp16")];
            tensor<int32, [1]> input_221_axes_0 = const()[name = tensor<string, []>("input_221_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244596608)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244599232)))];
            tensor<fp16, [1, 77, 1280]> input_221_cast_fp16 = layer_norm(axes = input_221_axes_0, beta = text_encoder_text_model_encoder_layers_13_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_13_layer_norm2_weight_to_fp16, x = input_219_cast_fp16)[name = tensor<string, []>("input_221_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244601856))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(249517120))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_13_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(249517312)))];
            tensor<fp16, [1, 77, 5120]> linear_82_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_13_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16_palettized, x = input_221_cast_fp16)[name = tensor<string, []>("linear_82_cast_fp16")];
            tensor<string, []> input_225_mode_0 = const()[name = tensor<string, []>("input_225_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_225_cast_fp16 = gelu(mode = input_225_mode_0, x = linear_82_cast_fp16)[name = tensor<string, []>("input_225_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_13_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(249527616))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(254442880))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(254443072)))];
            tensor<fp16, [1, 77, 1280]> linear_83_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_13_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_mlp_fc2_weight_to_fp16_palettized, x = input_225_cast_fp16)[name = tensor<string, []>("linear_83_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_227_cast_fp16 = add(x = input_219_cast_fp16, y = linear_83_cast_fp16)[name = tensor<string, []>("input_227_cast_fp16")];
            tensor<int32, [1]> hidden_states_85_axes_0 = const()[name = tensor<string, []>("hidden_states_85_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(254445696)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(254448320)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_85_cast_fp16 = layer_norm(axes = hidden_states_85_axes_0, beta = text_encoder_text_model_encoder_layers_14_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_14_layer_norm1_weight_to_fp16, x = input_227_cast_fp16)[name = tensor<string, []>("hidden_states_85_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(254450944))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(255679808))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(255680000)))];
            tensor<fp16, [1, 77, 1280]> linear_84_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_85_cast_fp16)[name = tensor<string, []>("linear_84_cast_fp16")];
            tensor<fp16, []> var_1366_to_fp16 = const()[name = tensor<string, []>("op_1366_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_89_cast_fp16 = mul(x = linear_84_cast_fp16, y = var_1366_to_fp16)[name = tensor<string, []>("tensor_89_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(255682624))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(256911488))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(256911680)))];
            tensor<fp16, [1, 77, 1280]> linear_85_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_85_cast_fp16)[name = tensor<string, []>("linear_85_cast_fp16")];
            tensor<int32, [4]> var_1371 = const()[name = tensor<string, []>("op_1371"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1372_cast_fp16 = reshape(shape = var_1371, x = linear_85_cast_fp16)[name = tensor<string, []>("op_1372_cast_fp16")];
            tensor<int32, [4]> var_1373_perm_0 = const()[name = tensor<string, []>("op_1373_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(256914304))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(258143168))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(258143360)))];
            tensor<fp16, [1, 77, 1280]> linear_86_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_85_cast_fp16)[name = tensor<string, []>("linear_86_cast_fp16")];
            tensor<int32, [4]> var_1378 = const()[name = tensor<string, []>("op_1378"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1379_cast_fp16 = reshape(shape = var_1378, x = linear_86_cast_fp16)[name = tensor<string, []>("op_1379_cast_fp16")];
            tensor<int32, [4]> var_1380_perm_0 = const()[name = tensor<string, []>("op_1380_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1387 = const()[name = tensor<string, []>("op_1387"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1388_cast_fp16 = reshape(shape = var_1387, x = tensor_89_cast_fp16)[name = tensor<string, []>("op_1388_cast_fp16")];
            tensor<int32, [4]> var_1389_perm_0 = const()[name = tensor<string, []>("op_1389_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1391 = const()[name = tensor<string, []>("op_1391"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1389_cast_fp16 = transpose(perm = var_1389_perm_0, x = var_1388_cast_fp16)[name = tensor<string, []>("transpose_71")];
            tensor<fp16, [20, 77, 64]> query_states_29_cast_fp16 = reshape(shape = var_1391, x = var_1389_cast_fp16)[name = tensor<string, []>("query_states_29_cast_fp16")];
            tensor<int32, [3]> var_1393 = const()[name = tensor<string, []>("op_1393"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1373_cast_fp16 = transpose(perm = var_1373_perm_0, x = var_1372_cast_fp16)[name = tensor<string, []>("transpose_70")];
            tensor<fp16, [20, 77, 64]> key_states_59_cast_fp16 = reshape(shape = var_1393, x = var_1373_cast_fp16)[name = tensor<string, []>("key_states_59_cast_fp16")];
            tensor<int32, [3]> var_1395 = const()[name = tensor<string, []>("op_1395"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1380_cast_fp16 = transpose(perm = var_1380_perm_0, x = var_1379_cast_fp16)[name = tensor<string, []>("transpose_69")];
            tensor<fp16, [20, 77, 64]> value_states_59_cast_fp16 = reshape(shape = var_1395, x = var_1380_cast_fp16)[name = tensor<string, []>("value_states_59_cast_fp16")];
            tensor<bool, []> attn_weights_85_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_85_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_85_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_85_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_85_cast_fp16 = matmul(transpose_x = attn_weights_85_transpose_x_1, transpose_y = attn_weights_85_transpose_y_1, x = query_states_29_cast_fp16, y = key_states_59_cast_fp16)[name = tensor<string, []>("attn_weights_85_cast_fp16")];
            tensor<int32, [4]> var_1400 = const()[name = tensor<string, []>("op_1400"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1401_cast_fp16 = reshape(shape = var_1400, x = attn_weights_85_cast_fp16)[name = tensor<string, []>("op_1401_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_87_cast_fp16 = add(x = var_1401_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_87_cast_fp16")];
            tensor<int32, [3]> var_1406 = const()[name = tensor<string, []>("op_1406"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_229_cast_fp16 = reshape(shape = var_1406, x = attn_weights_87_cast_fp16)[name = tensor<string, []>("input_229_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_231_cast_fp16 = softmax(axis = var_5, x = input_229_cast_fp16)[name = tensor<string, []>("input_231_cast_fp16")];
            tensor<bool, []> attn_output_85_transpose_x_0 = const()[name = tensor<string, []>("attn_output_85_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_85_transpose_y_0 = const()[name = tensor<string, []>("attn_output_85_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_85_cast_fp16 = matmul(transpose_x = attn_output_85_transpose_x_0, transpose_y = attn_output_85_transpose_y_0, x = input_231_cast_fp16, y = value_states_59_cast_fp16)[name = tensor<string, []>("attn_output_85_cast_fp16")];
            tensor<int32, [4]> var_1411 = const()[name = tensor<string, []>("op_1411"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_87_cast_fp16 = reshape(shape = var_1411, x = attn_output_85_cast_fp16)[name = tensor<string, []>("attn_output_87_cast_fp16")];
            tensor<int32, [4]> attn_output_89_perm_0 = const()[name = tensor<string, []>("attn_output_89_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1414 = const()[name = tensor<string, []>("op_1414"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_89_cast_fp16 = transpose(perm = attn_output_89_perm_0, x = attn_output_87_cast_fp16)[name = tensor<string, []>("transpose_68")];
            tensor<fp16, [1, 77, 1280]> input_233_cast_fp16 = reshape(shape = var_1414, x = attn_output_89_cast_fp16)[name = tensor<string, []>("input_233_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(258145984))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(259374848))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(259375040)))];
            tensor<fp16, [1, 77, 1280]> linear_87_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16_palettized, x = input_233_cast_fp16)[name = tensor<string, []>("linear_87_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_235_cast_fp16 = add(x = input_227_cast_fp16, y = linear_87_cast_fp16)[name = tensor<string, []>("input_235_cast_fp16")];
            tensor<int32, [1]> input_237_axes_0 = const()[name = tensor<string, []>("input_237_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(259377664)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(259380288)))];
            tensor<fp16, [1, 77, 1280]> input_237_cast_fp16 = layer_norm(axes = input_237_axes_0, beta = text_encoder_text_model_encoder_layers_14_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_14_layer_norm2_weight_to_fp16, x = input_235_cast_fp16)[name = tensor<string, []>("input_237_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(259382912))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(264298176))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_14_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(264298368)))];
            tensor<fp16, [1, 77, 5120]> linear_88_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_14_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16_palettized, x = input_237_cast_fp16)[name = tensor<string, []>("linear_88_cast_fp16")];
            tensor<string, []> input_241_mode_0 = const()[name = tensor<string, []>("input_241_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_241_cast_fp16 = gelu(mode = input_241_mode_0, x = linear_88_cast_fp16)[name = tensor<string, []>("input_241_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_14_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(264308672))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(269223936))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(269224128)))];
            tensor<fp16, [1, 77, 1280]> linear_89_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_14_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_mlp_fc2_weight_to_fp16_palettized, x = input_241_cast_fp16)[name = tensor<string, []>("linear_89_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_243_cast_fp16 = add(x = input_235_cast_fp16, y = linear_89_cast_fp16)[name = tensor<string, []>("input_243_cast_fp16")];
            tensor<int32, [1]> hidden_states_91_axes_0 = const()[name = tensor<string, []>("hidden_states_91_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(269226752)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(269229376)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_91_cast_fp16 = layer_norm(axes = hidden_states_91_axes_0, beta = text_encoder_text_model_encoder_layers_15_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_15_layer_norm1_weight_to_fp16, x = input_243_cast_fp16)[name = tensor<string, []>("hidden_states_91_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(269232000))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(270460864))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(270461056)))];
            tensor<fp16, [1, 77, 1280]> linear_90_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_91_cast_fp16)[name = tensor<string, []>("linear_90_cast_fp16")];
            tensor<fp16, []> var_1453_to_fp16 = const()[name = tensor<string, []>("op_1453_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_95_cast_fp16 = mul(x = linear_90_cast_fp16, y = var_1453_to_fp16)[name = tensor<string, []>("tensor_95_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(270463680))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(271692544))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(271692736)))];
            tensor<fp16, [1, 77, 1280]> linear_91_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_91_cast_fp16)[name = tensor<string, []>("linear_91_cast_fp16")];
            tensor<int32, [4]> var_1458 = const()[name = tensor<string, []>("op_1458"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1459_cast_fp16 = reshape(shape = var_1458, x = linear_91_cast_fp16)[name = tensor<string, []>("op_1459_cast_fp16")];
            tensor<int32, [4]> var_1460_perm_0 = const()[name = tensor<string, []>("op_1460_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(271695360))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(272924224))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(272924416)))];
            tensor<fp16, [1, 77, 1280]> linear_92_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_91_cast_fp16)[name = tensor<string, []>("linear_92_cast_fp16")];
            tensor<int32, [4]> var_1465 = const()[name = tensor<string, []>("op_1465"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1466_cast_fp16 = reshape(shape = var_1465, x = linear_92_cast_fp16)[name = tensor<string, []>("op_1466_cast_fp16")];
            tensor<int32, [4]> var_1467_perm_0 = const()[name = tensor<string, []>("op_1467_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1474 = const()[name = tensor<string, []>("op_1474"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1475_cast_fp16 = reshape(shape = var_1474, x = tensor_95_cast_fp16)[name = tensor<string, []>("op_1475_cast_fp16")];
            tensor<int32, [4]> var_1476_perm_0 = const()[name = tensor<string, []>("op_1476_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1478 = const()[name = tensor<string, []>("op_1478"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1476_cast_fp16 = transpose(perm = var_1476_perm_0, x = var_1475_cast_fp16)[name = tensor<string, []>("transpose_67")];
            tensor<fp16, [20, 77, 64]> query_states_31_cast_fp16 = reshape(shape = var_1478, x = var_1476_cast_fp16)[name = tensor<string, []>("query_states_31_cast_fp16")];
            tensor<int32, [3]> var_1480 = const()[name = tensor<string, []>("op_1480"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1460_cast_fp16 = transpose(perm = var_1460_perm_0, x = var_1459_cast_fp16)[name = tensor<string, []>("transpose_66")];
            tensor<fp16, [20, 77, 64]> key_states_63_cast_fp16 = reshape(shape = var_1480, x = var_1460_cast_fp16)[name = tensor<string, []>("key_states_63_cast_fp16")];
            tensor<int32, [3]> var_1482 = const()[name = tensor<string, []>("op_1482"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1467_cast_fp16 = transpose(perm = var_1467_perm_0, x = var_1466_cast_fp16)[name = tensor<string, []>("transpose_65")];
            tensor<fp16, [20, 77, 64]> value_states_63_cast_fp16 = reshape(shape = var_1482, x = var_1467_cast_fp16)[name = tensor<string, []>("value_states_63_cast_fp16")];
            tensor<bool, []> attn_weights_91_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_91_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_91_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_91_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_91_cast_fp16 = matmul(transpose_x = attn_weights_91_transpose_x_1, transpose_y = attn_weights_91_transpose_y_1, x = query_states_31_cast_fp16, y = key_states_63_cast_fp16)[name = tensor<string, []>("attn_weights_91_cast_fp16")];
            tensor<int32, [4]> var_1487 = const()[name = tensor<string, []>("op_1487"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1488_cast_fp16 = reshape(shape = var_1487, x = attn_weights_91_cast_fp16)[name = tensor<string, []>("op_1488_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_93_cast_fp16 = add(x = var_1488_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_93_cast_fp16")];
            tensor<int32, [3]> var_1493 = const()[name = tensor<string, []>("op_1493"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_245_cast_fp16 = reshape(shape = var_1493, x = attn_weights_93_cast_fp16)[name = tensor<string, []>("input_245_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_247_cast_fp16 = softmax(axis = var_5, x = input_245_cast_fp16)[name = tensor<string, []>("input_247_cast_fp16")];
            tensor<bool, []> attn_output_91_transpose_x_0 = const()[name = tensor<string, []>("attn_output_91_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_91_transpose_y_0 = const()[name = tensor<string, []>("attn_output_91_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_91_cast_fp16 = matmul(transpose_x = attn_output_91_transpose_x_0, transpose_y = attn_output_91_transpose_y_0, x = input_247_cast_fp16, y = value_states_63_cast_fp16)[name = tensor<string, []>("attn_output_91_cast_fp16")];
            tensor<int32, [4]> var_1498 = const()[name = tensor<string, []>("op_1498"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_93_cast_fp16 = reshape(shape = var_1498, x = attn_output_91_cast_fp16)[name = tensor<string, []>("attn_output_93_cast_fp16")];
            tensor<int32, [4]> attn_output_95_perm_0 = const()[name = tensor<string, []>("attn_output_95_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1501 = const()[name = tensor<string, []>("op_1501"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_95_cast_fp16 = transpose(perm = attn_output_95_perm_0, x = attn_output_93_cast_fp16)[name = tensor<string, []>("transpose_64")];
            tensor<fp16, [1, 77, 1280]> input_249_cast_fp16 = reshape(shape = var_1501, x = attn_output_95_cast_fp16)[name = tensor<string, []>("input_249_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(272927040))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(274155904))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(274156096)))];
            tensor<fp16, [1, 77, 1280]> linear_93_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16_palettized, x = input_249_cast_fp16)[name = tensor<string, []>("linear_93_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_251_cast_fp16 = add(x = input_243_cast_fp16, y = linear_93_cast_fp16)[name = tensor<string, []>("input_251_cast_fp16")];
            tensor<int32, [1]> input_253_axes_0 = const()[name = tensor<string, []>("input_253_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(274158720)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(274161344)))];
            tensor<fp16, [1, 77, 1280]> input_253_cast_fp16 = layer_norm(axes = input_253_axes_0, beta = text_encoder_text_model_encoder_layers_15_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_15_layer_norm2_weight_to_fp16, x = input_251_cast_fp16)[name = tensor<string, []>("input_253_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(274163968))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(279079232))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_15_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(279079424)))];
            tensor<fp16, [1, 77, 5120]> linear_94_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_15_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16_palettized, x = input_253_cast_fp16)[name = tensor<string, []>("linear_94_cast_fp16")];
            tensor<string, []> input_257_mode_0 = const()[name = tensor<string, []>("input_257_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_257_cast_fp16 = gelu(mode = input_257_mode_0, x = linear_94_cast_fp16)[name = tensor<string, []>("input_257_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_15_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(279089728))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284004992))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284005184)))];
            tensor<fp16, [1, 77, 1280]> linear_95_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_15_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_mlp_fc2_weight_to_fp16_palettized, x = input_257_cast_fp16)[name = tensor<string, []>("linear_95_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_259_cast_fp16 = add(x = input_251_cast_fp16, y = linear_95_cast_fp16)[name = tensor<string, []>("input_259_cast_fp16")];
            tensor<int32, [1]> hidden_states_97_axes_0 = const()[name = tensor<string, []>("hidden_states_97_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284007808)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284010432)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_97_cast_fp16 = layer_norm(axes = hidden_states_97_axes_0, beta = text_encoder_text_model_encoder_layers_16_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_16_layer_norm1_weight_to_fp16, x = input_259_cast_fp16)[name = tensor<string, []>("hidden_states_97_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284013056))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(285241920))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(285242112)))];
            tensor<fp16, [1, 77, 1280]> linear_96_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_97_cast_fp16)[name = tensor<string, []>("linear_96_cast_fp16")];
            tensor<fp16, []> var_1540_to_fp16 = const()[name = tensor<string, []>("op_1540_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_101_cast_fp16 = mul(x = linear_96_cast_fp16, y = var_1540_to_fp16)[name = tensor<string, []>("tensor_101_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(285244736))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(286473600))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(286473792)))];
            tensor<fp16, [1, 77, 1280]> linear_97_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_97_cast_fp16)[name = tensor<string, []>("linear_97_cast_fp16")];
            tensor<int32, [4]> var_1545 = const()[name = tensor<string, []>("op_1545"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1546_cast_fp16 = reshape(shape = var_1545, x = linear_97_cast_fp16)[name = tensor<string, []>("op_1546_cast_fp16")];
            tensor<int32, [4]> var_1547_perm_0 = const()[name = tensor<string, []>("op_1547_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(286476416))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(287705280))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(287705472)))];
            tensor<fp16, [1, 77, 1280]> linear_98_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_97_cast_fp16)[name = tensor<string, []>("linear_98_cast_fp16")];
            tensor<int32, [4]> var_1552 = const()[name = tensor<string, []>("op_1552"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1553_cast_fp16 = reshape(shape = var_1552, x = linear_98_cast_fp16)[name = tensor<string, []>("op_1553_cast_fp16")];
            tensor<int32, [4]> var_1554_perm_0 = const()[name = tensor<string, []>("op_1554_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1561 = const()[name = tensor<string, []>("op_1561"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1562_cast_fp16 = reshape(shape = var_1561, x = tensor_101_cast_fp16)[name = tensor<string, []>("op_1562_cast_fp16")];
            tensor<int32, [4]> var_1563_perm_0 = const()[name = tensor<string, []>("op_1563_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1565 = const()[name = tensor<string, []>("op_1565"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1563_cast_fp16 = transpose(perm = var_1563_perm_0, x = var_1562_cast_fp16)[name = tensor<string, []>("transpose_63")];
            tensor<fp16, [20, 77, 64]> query_states_33_cast_fp16 = reshape(shape = var_1565, x = var_1563_cast_fp16)[name = tensor<string, []>("query_states_33_cast_fp16")];
            tensor<int32, [3]> var_1567 = const()[name = tensor<string, []>("op_1567"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1547_cast_fp16 = transpose(perm = var_1547_perm_0, x = var_1546_cast_fp16)[name = tensor<string, []>("transpose_62")];
            tensor<fp16, [20, 77, 64]> key_states_67_cast_fp16 = reshape(shape = var_1567, x = var_1547_cast_fp16)[name = tensor<string, []>("key_states_67_cast_fp16")];
            tensor<int32, [3]> var_1569 = const()[name = tensor<string, []>("op_1569"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1554_cast_fp16 = transpose(perm = var_1554_perm_0, x = var_1553_cast_fp16)[name = tensor<string, []>("transpose_61")];
            tensor<fp16, [20, 77, 64]> value_states_67_cast_fp16 = reshape(shape = var_1569, x = var_1554_cast_fp16)[name = tensor<string, []>("value_states_67_cast_fp16")];
            tensor<bool, []> attn_weights_97_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_97_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_97_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_97_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_97_cast_fp16 = matmul(transpose_x = attn_weights_97_transpose_x_1, transpose_y = attn_weights_97_transpose_y_1, x = query_states_33_cast_fp16, y = key_states_67_cast_fp16)[name = tensor<string, []>("attn_weights_97_cast_fp16")];
            tensor<int32, [4]> var_1574 = const()[name = tensor<string, []>("op_1574"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1575_cast_fp16 = reshape(shape = var_1574, x = attn_weights_97_cast_fp16)[name = tensor<string, []>("op_1575_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_99_cast_fp16 = add(x = var_1575_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_99_cast_fp16")];
            tensor<int32, [3]> var_1580 = const()[name = tensor<string, []>("op_1580"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_261_cast_fp16 = reshape(shape = var_1580, x = attn_weights_99_cast_fp16)[name = tensor<string, []>("input_261_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_263_cast_fp16 = softmax(axis = var_5, x = input_261_cast_fp16)[name = tensor<string, []>("input_263_cast_fp16")];
            tensor<bool, []> attn_output_97_transpose_x_0 = const()[name = tensor<string, []>("attn_output_97_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_97_transpose_y_0 = const()[name = tensor<string, []>("attn_output_97_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_97_cast_fp16 = matmul(transpose_x = attn_output_97_transpose_x_0, transpose_y = attn_output_97_transpose_y_0, x = input_263_cast_fp16, y = value_states_67_cast_fp16)[name = tensor<string, []>("attn_output_97_cast_fp16")];
            tensor<int32, [4]> var_1585 = const()[name = tensor<string, []>("op_1585"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_99_cast_fp16 = reshape(shape = var_1585, x = attn_output_97_cast_fp16)[name = tensor<string, []>("attn_output_99_cast_fp16")];
            tensor<int32, [4]> attn_output_101_perm_0 = const()[name = tensor<string, []>("attn_output_101_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1588 = const()[name = tensor<string, []>("op_1588"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_101_cast_fp16 = transpose(perm = attn_output_101_perm_0, x = attn_output_99_cast_fp16)[name = tensor<string, []>("transpose_60")];
            tensor<fp16, [1, 77, 1280]> input_265_cast_fp16 = reshape(shape = var_1588, x = attn_output_101_cast_fp16)[name = tensor<string, []>("input_265_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(287708096))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(288936960))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(288937152)))];
            tensor<fp16, [1, 77, 1280]> linear_99_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16_palettized, x = input_265_cast_fp16)[name = tensor<string, []>("linear_99_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_267_cast_fp16 = add(x = input_259_cast_fp16, y = linear_99_cast_fp16)[name = tensor<string, []>("input_267_cast_fp16")];
            tensor<int32, [1]> input_269_axes_0 = const()[name = tensor<string, []>("input_269_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(288939776)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(288942400)))];
            tensor<fp16, [1, 77, 1280]> input_269_cast_fp16 = layer_norm(axes = input_269_axes_0, beta = text_encoder_text_model_encoder_layers_16_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_16_layer_norm2_weight_to_fp16, x = input_267_cast_fp16)[name = tensor<string, []>("input_269_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(288945024))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(293860288))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_16_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(293860480)))];
            tensor<fp16, [1, 77, 5120]> linear_100_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_16_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16_palettized, x = input_269_cast_fp16)[name = tensor<string, []>("linear_100_cast_fp16")];
            tensor<string, []> input_273_mode_0 = const()[name = tensor<string, []>("input_273_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_273_cast_fp16 = gelu(mode = input_273_mode_0, x = linear_100_cast_fp16)[name = tensor<string, []>("input_273_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_16_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(293870784))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(298786048))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(298786240)))];
            tensor<fp16, [1, 77, 1280]> linear_101_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_16_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_mlp_fc2_weight_to_fp16_palettized, x = input_273_cast_fp16)[name = tensor<string, []>("linear_101_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_275_cast_fp16 = add(x = input_267_cast_fp16, y = linear_101_cast_fp16)[name = tensor<string, []>("input_275_cast_fp16")];
            tensor<int32, [1]> hidden_states_103_axes_0 = const()[name = tensor<string, []>("hidden_states_103_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(298788864)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(298791488)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_103_cast_fp16 = layer_norm(axes = hidden_states_103_axes_0, beta = text_encoder_text_model_encoder_layers_17_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_17_layer_norm1_weight_to_fp16, x = input_275_cast_fp16)[name = tensor<string, []>("hidden_states_103_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(298794112))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(300022976))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(300023168)))];
            tensor<fp16, [1, 77, 1280]> linear_102_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_103_cast_fp16)[name = tensor<string, []>("linear_102_cast_fp16")];
            tensor<fp16, []> var_1627_to_fp16 = const()[name = tensor<string, []>("op_1627_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_107_cast_fp16 = mul(x = linear_102_cast_fp16, y = var_1627_to_fp16)[name = tensor<string, []>("tensor_107_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(300025792))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(301254656))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(301254848)))];
            tensor<fp16, [1, 77, 1280]> linear_103_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_103_cast_fp16)[name = tensor<string, []>("linear_103_cast_fp16")];
            tensor<int32, [4]> var_1632 = const()[name = tensor<string, []>("op_1632"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1633_cast_fp16 = reshape(shape = var_1632, x = linear_103_cast_fp16)[name = tensor<string, []>("op_1633_cast_fp16")];
            tensor<int32, [4]> var_1634_perm_0 = const()[name = tensor<string, []>("op_1634_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(301257472))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(302486336))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(302486528)))];
            tensor<fp16, [1, 77, 1280]> linear_104_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_103_cast_fp16)[name = tensor<string, []>("linear_104_cast_fp16")];
            tensor<int32, [4]> var_1639 = const()[name = tensor<string, []>("op_1639"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1640_cast_fp16 = reshape(shape = var_1639, x = linear_104_cast_fp16)[name = tensor<string, []>("op_1640_cast_fp16")];
            tensor<int32, [4]> var_1641_perm_0 = const()[name = tensor<string, []>("op_1641_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1648 = const()[name = tensor<string, []>("op_1648"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1649_cast_fp16 = reshape(shape = var_1648, x = tensor_107_cast_fp16)[name = tensor<string, []>("op_1649_cast_fp16")];
            tensor<int32, [4]> var_1650_perm_0 = const()[name = tensor<string, []>("op_1650_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1652 = const()[name = tensor<string, []>("op_1652"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1650_cast_fp16 = transpose(perm = var_1650_perm_0, x = var_1649_cast_fp16)[name = tensor<string, []>("transpose_59")];
            tensor<fp16, [20, 77, 64]> query_states_35_cast_fp16 = reshape(shape = var_1652, x = var_1650_cast_fp16)[name = tensor<string, []>("query_states_35_cast_fp16")];
            tensor<int32, [3]> var_1654 = const()[name = tensor<string, []>("op_1654"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1634_cast_fp16 = transpose(perm = var_1634_perm_0, x = var_1633_cast_fp16)[name = tensor<string, []>("transpose_58")];
            tensor<fp16, [20, 77, 64]> key_states_71_cast_fp16 = reshape(shape = var_1654, x = var_1634_cast_fp16)[name = tensor<string, []>("key_states_71_cast_fp16")];
            tensor<int32, [3]> var_1656 = const()[name = tensor<string, []>("op_1656"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1641_cast_fp16 = transpose(perm = var_1641_perm_0, x = var_1640_cast_fp16)[name = tensor<string, []>("transpose_57")];
            tensor<fp16, [20, 77, 64]> value_states_71_cast_fp16 = reshape(shape = var_1656, x = var_1641_cast_fp16)[name = tensor<string, []>("value_states_71_cast_fp16")];
            tensor<bool, []> attn_weights_103_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_103_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_103_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_103_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_103_cast_fp16 = matmul(transpose_x = attn_weights_103_transpose_x_1, transpose_y = attn_weights_103_transpose_y_1, x = query_states_35_cast_fp16, y = key_states_71_cast_fp16)[name = tensor<string, []>("attn_weights_103_cast_fp16")];
            tensor<int32, [4]> var_1661 = const()[name = tensor<string, []>("op_1661"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1662_cast_fp16 = reshape(shape = var_1661, x = attn_weights_103_cast_fp16)[name = tensor<string, []>("op_1662_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_105_cast_fp16 = add(x = var_1662_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_105_cast_fp16")];
            tensor<int32, [3]> var_1667 = const()[name = tensor<string, []>("op_1667"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_277_cast_fp16 = reshape(shape = var_1667, x = attn_weights_105_cast_fp16)[name = tensor<string, []>("input_277_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_279_cast_fp16 = softmax(axis = var_5, x = input_277_cast_fp16)[name = tensor<string, []>("input_279_cast_fp16")];
            tensor<bool, []> attn_output_103_transpose_x_0 = const()[name = tensor<string, []>("attn_output_103_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_103_transpose_y_0 = const()[name = tensor<string, []>("attn_output_103_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_103_cast_fp16 = matmul(transpose_x = attn_output_103_transpose_x_0, transpose_y = attn_output_103_transpose_y_0, x = input_279_cast_fp16, y = value_states_71_cast_fp16)[name = tensor<string, []>("attn_output_103_cast_fp16")];
            tensor<int32, [4]> var_1672 = const()[name = tensor<string, []>("op_1672"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_105_cast_fp16 = reshape(shape = var_1672, x = attn_output_103_cast_fp16)[name = tensor<string, []>("attn_output_105_cast_fp16")];
            tensor<int32, [4]> attn_output_107_perm_0 = const()[name = tensor<string, []>("attn_output_107_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1675 = const()[name = tensor<string, []>("op_1675"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_107_cast_fp16 = transpose(perm = attn_output_107_perm_0, x = attn_output_105_cast_fp16)[name = tensor<string, []>("transpose_56")];
            tensor<fp16, [1, 77, 1280]> input_281_cast_fp16 = reshape(shape = var_1675, x = attn_output_107_cast_fp16)[name = tensor<string, []>("input_281_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(302489152))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(303718016))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(303718208)))];
            tensor<fp16, [1, 77, 1280]> linear_105_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16_palettized, x = input_281_cast_fp16)[name = tensor<string, []>("linear_105_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_283_cast_fp16 = add(x = input_275_cast_fp16, y = linear_105_cast_fp16)[name = tensor<string, []>("input_283_cast_fp16")];
            tensor<int32, [1]> input_285_axes_0 = const()[name = tensor<string, []>("input_285_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(303720832)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(303723456)))];
            tensor<fp16, [1, 77, 1280]> input_285_cast_fp16 = layer_norm(axes = input_285_axes_0, beta = text_encoder_text_model_encoder_layers_17_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_17_layer_norm2_weight_to_fp16, x = input_283_cast_fp16)[name = tensor<string, []>("input_285_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(303726080))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(308641344))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_17_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(308641536)))];
            tensor<fp16, [1, 77, 5120]> linear_106_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_17_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16_palettized, x = input_285_cast_fp16)[name = tensor<string, []>("linear_106_cast_fp16")];
            tensor<string, []> input_289_mode_0 = const()[name = tensor<string, []>("input_289_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_289_cast_fp16 = gelu(mode = input_289_mode_0, x = linear_106_cast_fp16)[name = tensor<string, []>("input_289_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_17_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(308651840))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(313567104))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(313567296)))];
            tensor<fp16, [1, 77, 1280]> linear_107_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_17_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_mlp_fc2_weight_to_fp16_palettized, x = input_289_cast_fp16)[name = tensor<string, []>("linear_107_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_291_cast_fp16 = add(x = input_283_cast_fp16, y = linear_107_cast_fp16)[name = tensor<string, []>("input_291_cast_fp16")];
            tensor<int32, [1]> hidden_states_109_axes_0 = const()[name = tensor<string, []>("hidden_states_109_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(313569920)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(313572544)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_109_cast_fp16 = layer_norm(axes = hidden_states_109_axes_0, beta = text_encoder_text_model_encoder_layers_18_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_18_layer_norm1_weight_to_fp16, x = input_291_cast_fp16)[name = tensor<string, []>("hidden_states_109_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(313575168))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(314804032))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(314804224)))];
            tensor<fp16, [1, 77, 1280]> linear_108_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_109_cast_fp16)[name = tensor<string, []>("linear_108_cast_fp16")];
            tensor<fp16, []> var_1714_to_fp16 = const()[name = tensor<string, []>("op_1714_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_113_cast_fp16 = mul(x = linear_108_cast_fp16, y = var_1714_to_fp16)[name = tensor<string, []>("tensor_113_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(314806848))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(316035712))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(316035904)))];
            tensor<fp16, [1, 77, 1280]> linear_109_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_109_cast_fp16)[name = tensor<string, []>("linear_109_cast_fp16")];
            tensor<int32, [4]> var_1719 = const()[name = tensor<string, []>("op_1719"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1720_cast_fp16 = reshape(shape = var_1719, x = linear_109_cast_fp16)[name = tensor<string, []>("op_1720_cast_fp16")];
            tensor<int32, [4]> var_1721_perm_0 = const()[name = tensor<string, []>("op_1721_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(316038528))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(317267392))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(317267584)))];
            tensor<fp16, [1, 77, 1280]> linear_110_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_109_cast_fp16)[name = tensor<string, []>("linear_110_cast_fp16")];
            tensor<int32, [4]> var_1726 = const()[name = tensor<string, []>("op_1726"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1727_cast_fp16 = reshape(shape = var_1726, x = linear_110_cast_fp16)[name = tensor<string, []>("op_1727_cast_fp16")];
            tensor<int32, [4]> var_1728_perm_0 = const()[name = tensor<string, []>("op_1728_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1735 = const()[name = tensor<string, []>("op_1735"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1736_cast_fp16 = reshape(shape = var_1735, x = tensor_113_cast_fp16)[name = tensor<string, []>("op_1736_cast_fp16")];
            tensor<int32, [4]> var_1737_perm_0 = const()[name = tensor<string, []>("op_1737_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1739 = const()[name = tensor<string, []>("op_1739"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1737_cast_fp16 = transpose(perm = var_1737_perm_0, x = var_1736_cast_fp16)[name = tensor<string, []>("transpose_55")];
            tensor<fp16, [20, 77, 64]> query_states_37_cast_fp16 = reshape(shape = var_1739, x = var_1737_cast_fp16)[name = tensor<string, []>("query_states_37_cast_fp16")];
            tensor<int32, [3]> var_1741 = const()[name = tensor<string, []>("op_1741"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1721_cast_fp16 = transpose(perm = var_1721_perm_0, x = var_1720_cast_fp16)[name = tensor<string, []>("transpose_54")];
            tensor<fp16, [20, 77, 64]> key_states_75_cast_fp16 = reshape(shape = var_1741, x = var_1721_cast_fp16)[name = tensor<string, []>("key_states_75_cast_fp16")];
            tensor<int32, [3]> var_1743 = const()[name = tensor<string, []>("op_1743"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1728_cast_fp16 = transpose(perm = var_1728_perm_0, x = var_1727_cast_fp16)[name = tensor<string, []>("transpose_53")];
            tensor<fp16, [20, 77, 64]> value_states_75_cast_fp16 = reshape(shape = var_1743, x = var_1728_cast_fp16)[name = tensor<string, []>("value_states_75_cast_fp16")];
            tensor<bool, []> attn_weights_109_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_109_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_109_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_109_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_109_cast_fp16 = matmul(transpose_x = attn_weights_109_transpose_x_1, transpose_y = attn_weights_109_transpose_y_1, x = query_states_37_cast_fp16, y = key_states_75_cast_fp16)[name = tensor<string, []>("attn_weights_109_cast_fp16")];
            tensor<int32, [4]> var_1748 = const()[name = tensor<string, []>("op_1748"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1749_cast_fp16 = reshape(shape = var_1748, x = attn_weights_109_cast_fp16)[name = tensor<string, []>("op_1749_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_111_cast_fp16 = add(x = var_1749_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_111_cast_fp16")];
            tensor<int32, [3]> var_1754 = const()[name = tensor<string, []>("op_1754"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_293_cast_fp16 = reshape(shape = var_1754, x = attn_weights_111_cast_fp16)[name = tensor<string, []>("input_293_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_295_cast_fp16 = softmax(axis = var_5, x = input_293_cast_fp16)[name = tensor<string, []>("input_295_cast_fp16")];
            tensor<bool, []> attn_output_109_transpose_x_0 = const()[name = tensor<string, []>("attn_output_109_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_109_transpose_y_0 = const()[name = tensor<string, []>("attn_output_109_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_109_cast_fp16 = matmul(transpose_x = attn_output_109_transpose_x_0, transpose_y = attn_output_109_transpose_y_0, x = input_295_cast_fp16, y = value_states_75_cast_fp16)[name = tensor<string, []>("attn_output_109_cast_fp16")];
            tensor<int32, [4]> var_1759 = const()[name = tensor<string, []>("op_1759"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_111_cast_fp16 = reshape(shape = var_1759, x = attn_output_109_cast_fp16)[name = tensor<string, []>("attn_output_111_cast_fp16")];
            tensor<int32, [4]> attn_output_113_perm_0 = const()[name = tensor<string, []>("attn_output_113_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1762 = const()[name = tensor<string, []>("op_1762"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_113_cast_fp16 = transpose(perm = attn_output_113_perm_0, x = attn_output_111_cast_fp16)[name = tensor<string, []>("transpose_52")];
            tensor<fp16, [1, 77, 1280]> input_297_cast_fp16 = reshape(shape = var_1762, x = attn_output_113_cast_fp16)[name = tensor<string, []>("input_297_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(317270208))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(318499072))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(318499264)))];
            tensor<fp16, [1, 77, 1280]> linear_111_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16_palettized, x = input_297_cast_fp16)[name = tensor<string, []>("linear_111_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_299_cast_fp16 = add(x = input_291_cast_fp16, y = linear_111_cast_fp16)[name = tensor<string, []>("input_299_cast_fp16")];
            tensor<int32, [1]> input_301_axes_0 = const()[name = tensor<string, []>("input_301_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(318501888)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(318504512)))];
            tensor<fp16, [1, 77, 1280]> input_301_cast_fp16 = layer_norm(axes = input_301_axes_0, beta = text_encoder_text_model_encoder_layers_18_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_18_layer_norm2_weight_to_fp16, x = input_299_cast_fp16)[name = tensor<string, []>("input_301_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(318507136))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(323422400))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_18_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(323422592)))];
            tensor<fp16, [1, 77, 5120]> linear_112_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_18_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16_palettized, x = input_301_cast_fp16)[name = tensor<string, []>("linear_112_cast_fp16")];
            tensor<string, []> input_305_mode_0 = const()[name = tensor<string, []>("input_305_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_305_cast_fp16 = gelu(mode = input_305_mode_0, x = linear_112_cast_fp16)[name = tensor<string, []>("input_305_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_18_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(323432896))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(328348160))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(328348352)))];
            tensor<fp16, [1, 77, 1280]> linear_113_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_18_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_mlp_fc2_weight_to_fp16_palettized, x = input_305_cast_fp16)[name = tensor<string, []>("linear_113_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_307_cast_fp16 = add(x = input_299_cast_fp16, y = linear_113_cast_fp16)[name = tensor<string, []>("input_307_cast_fp16")];
            tensor<int32, [1]> hidden_states_115_axes_0 = const()[name = tensor<string, []>("hidden_states_115_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(328350976)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(328353600)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_115_cast_fp16 = layer_norm(axes = hidden_states_115_axes_0, beta = text_encoder_text_model_encoder_layers_19_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_19_layer_norm1_weight_to_fp16, x = input_307_cast_fp16)[name = tensor<string, []>("hidden_states_115_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(328356224))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(329585088))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(329585280)))];
            tensor<fp16, [1, 77, 1280]> linear_114_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_115_cast_fp16)[name = tensor<string, []>("linear_114_cast_fp16")];
            tensor<fp16, []> var_1801_to_fp16 = const()[name = tensor<string, []>("op_1801_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_119_cast_fp16 = mul(x = linear_114_cast_fp16, y = var_1801_to_fp16)[name = tensor<string, []>("tensor_119_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(329587904))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(330816768))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(330816960)))];
            tensor<fp16, [1, 77, 1280]> linear_115_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_115_cast_fp16)[name = tensor<string, []>("linear_115_cast_fp16")];
            tensor<int32, [4]> var_1806 = const()[name = tensor<string, []>("op_1806"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1807_cast_fp16 = reshape(shape = var_1806, x = linear_115_cast_fp16)[name = tensor<string, []>("op_1807_cast_fp16")];
            tensor<int32, [4]> var_1808_perm_0 = const()[name = tensor<string, []>("op_1808_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(330819584))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(332048448))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(332048640)))];
            tensor<fp16, [1, 77, 1280]> linear_116_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_115_cast_fp16)[name = tensor<string, []>("linear_116_cast_fp16")];
            tensor<int32, [4]> var_1813 = const()[name = tensor<string, []>("op_1813"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1814_cast_fp16 = reshape(shape = var_1813, x = linear_116_cast_fp16)[name = tensor<string, []>("op_1814_cast_fp16")];
            tensor<int32, [4]> var_1815_perm_0 = const()[name = tensor<string, []>("op_1815_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1822 = const()[name = tensor<string, []>("op_1822"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1823_cast_fp16 = reshape(shape = var_1822, x = tensor_119_cast_fp16)[name = tensor<string, []>("op_1823_cast_fp16")];
            tensor<int32, [4]> var_1824_perm_0 = const()[name = tensor<string, []>("op_1824_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1826 = const()[name = tensor<string, []>("op_1826"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1824_cast_fp16 = transpose(perm = var_1824_perm_0, x = var_1823_cast_fp16)[name = tensor<string, []>("transpose_51")];
            tensor<fp16, [20, 77, 64]> query_states_39_cast_fp16 = reshape(shape = var_1826, x = var_1824_cast_fp16)[name = tensor<string, []>("query_states_39_cast_fp16")];
            tensor<int32, [3]> var_1828 = const()[name = tensor<string, []>("op_1828"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1808_cast_fp16 = transpose(perm = var_1808_perm_0, x = var_1807_cast_fp16)[name = tensor<string, []>("transpose_50")];
            tensor<fp16, [20, 77, 64]> key_states_79_cast_fp16 = reshape(shape = var_1828, x = var_1808_cast_fp16)[name = tensor<string, []>("key_states_79_cast_fp16")];
            tensor<int32, [3]> var_1830 = const()[name = tensor<string, []>("op_1830"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1815_cast_fp16 = transpose(perm = var_1815_perm_0, x = var_1814_cast_fp16)[name = tensor<string, []>("transpose_49")];
            tensor<fp16, [20, 77, 64]> value_states_79_cast_fp16 = reshape(shape = var_1830, x = var_1815_cast_fp16)[name = tensor<string, []>("value_states_79_cast_fp16")];
            tensor<bool, []> attn_weights_115_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_115_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_115_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_115_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_115_cast_fp16 = matmul(transpose_x = attn_weights_115_transpose_x_1, transpose_y = attn_weights_115_transpose_y_1, x = query_states_39_cast_fp16, y = key_states_79_cast_fp16)[name = tensor<string, []>("attn_weights_115_cast_fp16")];
            tensor<int32, [4]> var_1835 = const()[name = tensor<string, []>("op_1835"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1836_cast_fp16 = reshape(shape = var_1835, x = attn_weights_115_cast_fp16)[name = tensor<string, []>("op_1836_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_117_cast_fp16 = add(x = var_1836_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_117_cast_fp16")];
            tensor<int32, [3]> var_1841 = const()[name = tensor<string, []>("op_1841"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_309_cast_fp16 = reshape(shape = var_1841, x = attn_weights_117_cast_fp16)[name = tensor<string, []>("input_309_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_311_cast_fp16 = softmax(axis = var_5, x = input_309_cast_fp16)[name = tensor<string, []>("input_311_cast_fp16")];
            tensor<bool, []> attn_output_115_transpose_x_0 = const()[name = tensor<string, []>("attn_output_115_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_115_transpose_y_0 = const()[name = tensor<string, []>("attn_output_115_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_115_cast_fp16 = matmul(transpose_x = attn_output_115_transpose_x_0, transpose_y = attn_output_115_transpose_y_0, x = input_311_cast_fp16, y = value_states_79_cast_fp16)[name = tensor<string, []>("attn_output_115_cast_fp16")];
            tensor<int32, [4]> var_1846 = const()[name = tensor<string, []>("op_1846"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_117_cast_fp16 = reshape(shape = var_1846, x = attn_output_115_cast_fp16)[name = tensor<string, []>("attn_output_117_cast_fp16")];
            tensor<int32, [4]> attn_output_119_perm_0 = const()[name = tensor<string, []>("attn_output_119_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1849 = const()[name = tensor<string, []>("op_1849"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_119_cast_fp16 = transpose(perm = attn_output_119_perm_0, x = attn_output_117_cast_fp16)[name = tensor<string, []>("transpose_48")];
            tensor<fp16, [1, 77, 1280]> input_313_cast_fp16 = reshape(shape = var_1849, x = attn_output_119_cast_fp16)[name = tensor<string, []>("input_313_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(332051264))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(333280128))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(333280320)))];
            tensor<fp16, [1, 77, 1280]> linear_117_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16_palettized, x = input_313_cast_fp16)[name = tensor<string, []>("linear_117_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_315_cast_fp16 = add(x = input_307_cast_fp16, y = linear_117_cast_fp16)[name = tensor<string, []>("input_315_cast_fp16")];
            tensor<int32, [1]> input_317_axes_0 = const()[name = tensor<string, []>("input_317_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(333282944)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(333285568)))];
            tensor<fp16, [1, 77, 1280]> input_317_cast_fp16 = layer_norm(axes = input_317_axes_0, beta = text_encoder_text_model_encoder_layers_19_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_19_layer_norm2_weight_to_fp16, x = input_315_cast_fp16)[name = tensor<string, []>("input_317_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(333288192))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(338203456))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_19_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(338203648)))];
            tensor<fp16, [1, 77, 5120]> linear_118_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_19_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16_palettized, x = input_317_cast_fp16)[name = tensor<string, []>("linear_118_cast_fp16")];
            tensor<string, []> input_321_mode_0 = const()[name = tensor<string, []>("input_321_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_321_cast_fp16 = gelu(mode = input_321_mode_0, x = linear_118_cast_fp16)[name = tensor<string, []>("input_321_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_19_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(338213952))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(343129216))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(343129408)))];
            tensor<fp16, [1, 77, 1280]> linear_119_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_19_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_mlp_fc2_weight_to_fp16_palettized, x = input_321_cast_fp16)[name = tensor<string, []>("linear_119_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_323_cast_fp16 = add(x = input_315_cast_fp16, y = linear_119_cast_fp16)[name = tensor<string, []>("input_323_cast_fp16")];
            tensor<int32, [1]> hidden_states_121_axes_0 = const()[name = tensor<string, []>("hidden_states_121_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(343132032)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(343134656)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_121_cast_fp16 = layer_norm(axes = hidden_states_121_axes_0, beta = text_encoder_text_model_encoder_layers_20_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_20_layer_norm1_weight_to_fp16, x = input_323_cast_fp16)[name = tensor<string, []>("hidden_states_121_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(343137280))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(344366144))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(344366336)))];
            tensor<fp16, [1, 77, 1280]> linear_120_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_121_cast_fp16)[name = tensor<string, []>("linear_120_cast_fp16")];
            tensor<fp16, []> var_1888_to_fp16 = const()[name = tensor<string, []>("op_1888_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_125_cast_fp16 = mul(x = linear_120_cast_fp16, y = var_1888_to_fp16)[name = tensor<string, []>("tensor_125_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(344368960))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(345597824))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(345598016)))];
            tensor<fp16, [1, 77, 1280]> linear_121_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_121_cast_fp16)[name = tensor<string, []>("linear_121_cast_fp16")];
            tensor<int32, [4]> var_1893 = const()[name = tensor<string, []>("op_1893"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1894_cast_fp16 = reshape(shape = var_1893, x = linear_121_cast_fp16)[name = tensor<string, []>("op_1894_cast_fp16")];
            tensor<int32, [4]> var_1895_perm_0 = const()[name = tensor<string, []>("op_1895_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(345600640))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(346829504))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(346829696)))];
            tensor<fp16, [1, 77, 1280]> linear_122_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_121_cast_fp16)[name = tensor<string, []>("linear_122_cast_fp16")];
            tensor<int32, [4]> var_1900 = const()[name = tensor<string, []>("op_1900"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1901_cast_fp16 = reshape(shape = var_1900, x = linear_122_cast_fp16)[name = tensor<string, []>("op_1901_cast_fp16")];
            tensor<int32, [4]> var_1902_perm_0 = const()[name = tensor<string, []>("op_1902_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1909 = const()[name = tensor<string, []>("op_1909"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1910_cast_fp16 = reshape(shape = var_1909, x = tensor_125_cast_fp16)[name = tensor<string, []>("op_1910_cast_fp16")];
            tensor<int32, [4]> var_1911_perm_0 = const()[name = tensor<string, []>("op_1911_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1913 = const()[name = tensor<string, []>("op_1913"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1911_cast_fp16 = transpose(perm = var_1911_perm_0, x = var_1910_cast_fp16)[name = tensor<string, []>("transpose_47")];
            tensor<fp16, [20, 77, 64]> query_states_41_cast_fp16 = reshape(shape = var_1913, x = var_1911_cast_fp16)[name = tensor<string, []>("query_states_41_cast_fp16")];
            tensor<int32, [3]> var_1915 = const()[name = tensor<string, []>("op_1915"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1895_cast_fp16 = transpose(perm = var_1895_perm_0, x = var_1894_cast_fp16)[name = tensor<string, []>("transpose_46")];
            tensor<fp16, [20, 77, 64]> key_states_83_cast_fp16 = reshape(shape = var_1915, x = var_1895_cast_fp16)[name = tensor<string, []>("key_states_83_cast_fp16")];
            tensor<int32, [3]> var_1917 = const()[name = tensor<string, []>("op_1917"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1902_cast_fp16 = transpose(perm = var_1902_perm_0, x = var_1901_cast_fp16)[name = tensor<string, []>("transpose_45")];
            tensor<fp16, [20, 77, 64]> value_states_83_cast_fp16 = reshape(shape = var_1917, x = var_1902_cast_fp16)[name = tensor<string, []>("value_states_83_cast_fp16")];
            tensor<bool, []> attn_weights_121_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_121_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_121_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_121_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_121_cast_fp16 = matmul(transpose_x = attn_weights_121_transpose_x_1, transpose_y = attn_weights_121_transpose_y_1, x = query_states_41_cast_fp16, y = key_states_83_cast_fp16)[name = tensor<string, []>("attn_weights_121_cast_fp16")];
            tensor<int32, [4]> var_1922 = const()[name = tensor<string, []>("op_1922"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_1923_cast_fp16 = reshape(shape = var_1922, x = attn_weights_121_cast_fp16)[name = tensor<string, []>("op_1923_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_123_cast_fp16 = add(x = var_1923_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_123_cast_fp16")];
            tensor<int32, [3]> var_1928 = const()[name = tensor<string, []>("op_1928"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_325_cast_fp16 = reshape(shape = var_1928, x = attn_weights_123_cast_fp16)[name = tensor<string, []>("input_325_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_327_cast_fp16 = softmax(axis = var_5, x = input_325_cast_fp16)[name = tensor<string, []>("input_327_cast_fp16")];
            tensor<bool, []> attn_output_121_transpose_x_0 = const()[name = tensor<string, []>("attn_output_121_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_121_transpose_y_0 = const()[name = tensor<string, []>("attn_output_121_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_121_cast_fp16 = matmul(transpose_x = attn_output_121_transpose_x_0, transpose_y = attn_output_121_transpose_y_0, x = input_327_cast_fp16, y = value_states_83_cast_fp16)[name = tensor<string, []>("attn_output_121_cast_fp16")];
            tensor<int32, [4]> var_1933 = const()[name = tensor<string, []>("op_1933"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_123_cast_fp16 = reshape(shape = var_1933, x = attn_output_121_cast_fp16)[name = tensor<string, []>("attn_output_123_cast_fp16")];
            tensor<int32, [4]> attn_output_125_perm_0 = const()[name = tensor<string, []>("attn_output_125_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1936 = const()[name = tensor<string, []>("op_1936"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_125_cast_fp16 = transpose(perm = attn_output_125_perm_0, x = attn_output_123_cast_fp16)[name = tensor<string, []>("transpose_44")];
            tensor<fp16, [1, 77, 1280]> input_329_cast_fp16 = reshape(shape = var_1936, x = attn_output_125_cast_fp16)[name = tensor<string, []>("input_329_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(346832320))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(348061184))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(348061376)))];
            tensor<fp16, [1, 77, 1280]> linear_123_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16_palettized, x = input_329_cast_fp16)[name = tensor<string, []>("linear_123_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_331_cast_fp16 = add(x = input_323_cast_fp16, y = linear_123_cast_fp16)[name = tensor<string, []>("input_331_cast_fp16")];
            tensor<int32, [1]> input_333_axes_0 = const()[name = tensor<string, []>("input_333_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(348064000)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(348066624)))];
            tensor<fp16, [1, 77, 1280]> input_333_cast_fp16 = layer_norm(axes = input_333_axes_0, beta = text_encoder_text_model_encoder_layers_20_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_20_layer_norm2_weight_to_fp16, x = input_331_cast_fp16)[name = tensor<string, []>("input_333_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(348069248))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(352984512))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_20_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(352984704)))];
            tensor<fp16, [1, 77, 5120]> linear_124_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_20_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16_palettized, x = input_333_cast_fp16)[name = tensor<string, []>("linear_124_cast_fp16")];
            tensor<string, []> input_337_mode_0 = const()[name = tensor<string, []>("input_337_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_337_cast_fp16 = gelu(mode = input_337_mode_0, x = linear_124_cast_fp16)[name = tensor<string, []>("input_337_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_20_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(352995008))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(357910272))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(357910464)))];
            tensor<fp16, [1, 77, 1280]> linear_125_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_20_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_mlp_fc2_weight_to_fp16_palettized, x = input_337_cast_fp16)[name = tensor<string, []>("linear_125_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_339_cast_fp16 = add(x = input_331_cast_fp16, y = linear_125_cast_fp16)[name = tensor<string, []>("input_339_cast_fp16")];
            tensor<int32, [1]> hidden_states_127_axes_0 = const()[name = tensor<string, []>("hidden_states_127_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(357913088)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(357915712)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_127_cast_fp16 = layer_norm(axes = hidden_states_127_axes_0, beta = text_encoder_text_model_encoder_layers_21_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_21_layer_norm1_weight_to_fp16, x = input_339_cast_fp16)[name = tensor<string, []>("hidden_states_127_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(357918336))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(359147200))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(359147392)))];
            tensor<fp16, [1, 77, 1280]> linear_126_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_127_cast_fp16)[name = tensor<string, []>("linear_126_cast_fp16")];
            tensor<fp16, []> var_1975_to_fp16 = const()[name = tensor<string, []>("op_1975_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_131_cast_fp16 = mul(x = linear_126_cast_fp16, y = var_1975_to_fp16)[name = tensor<string, []>("tensor_131_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(359150016))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(360378880))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(360379072)))];
            tensor<fp16, [1, 77, 1280]> linear_127_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_127_cast_fp16)[name = tensor<string, []>("linear_127_cast_fp16")];
            tensor<int32, [4]> var_1980 = const()[name = tensor<string, []>("op_1980"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1981_cast_fp16 = reshape(shape = var_1980, x = linear_127_cast_fp16)[name = tensor<string, []>("op_1981_cast_fp16")];
            tensor<int32, [4]> var_1982_perm_0 = const()[name = tensor<string, []>("op_1982_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(360381696))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(361610560))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(361610752)))];
            tensor<fp16, [1, 77, 1280]> linear_128_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_127_cast_fp16)[name = tensor<string, []>("linear_128_cast_fp16")];
            tensor<int32, [4]> var_1987 = const()[name = tensor<string, []>("op_1987"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1988_cast_fp16 = reshape(shape = var_1987, x = linear_128_cast_fp16)[name = tensor<string, []>("op_1988_cast_fp16")];
            tensor<int32, [4]> var_1989_perm_0 = const()[name = tensor<string, []>("op_1989_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_1996 = const()[name = tensor<string, []>("op_1996"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_1997_cast_fp16 = reshape(shape = var_1996, x = tensor_131_cast_fp16)[name = tensor<string, []>("op_1997_cast_fp16")];
            tensor<int32, [4]> var_1998_perm_0 = const()[name = tensor<string, []>("op_1998_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2000 = const()[name = tensor<string, []>("op_2000"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1998_cast_fp16 = transpose(perm = var_1998_perm_0, x = var_1997_cast_fp16)[name = tensor<string, []>("transpose_43")];
            tensor<fp16, [20, 77, 64]> query_states_43_cast_fp16 = reshape(shape = var_2000, x = var_1998_cast_fp16)[name = tensor<string, []>("query_states_43_cast_fp16")];
            tensor<int32, [3]> var_2002 = const()[name = tensor<string, []>("op_2002"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1982_cast_fp16 = transpose(perm = var_1982_perm_0, x = var_1981_cast_fp16)[name = tensor<string, []>("transpose_42")];
            tensor<fp16, [20, 77, 64]> key_states_87_cast_fp16 = reshape(shape = var_2002, x = var_1982_cast_fp16)[name = tensor<string, []>("key_states_87_cast_fp16")];
            tensor<int32, [3]> var_2004 = const()[name = tensor<string, []>("op_2004"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_1989_cast_fp16 = transpose(perm = var_1989_perm_0, x = var_1988_cast_fp16)[name = tensor<string, []>("transpose_41")];
            tensor<fp16, [20, 77, 64]> value_states_87_cast_fp16 = reshape(shape = var_2004, x = var_1989_cast_fp16)[name = tensor<string, []>("value_states_87_cast_fp16")];
            tensor<bool, []> attn_weights_127_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_127_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_127_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_127_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_127_cast_fp16 = matmul(transpose_x = attn_weights_127_transpose_x_1, transpose_y = attn_weights_127_transpose_y_1, x = query_states_43_cast_fp16, y = key_states_87_cast_fp16)[name = tensor<string, []>("attn_weights_127_cast_fp16")];
            tensor<int32, [4]> var_2009 = const()[name = tensor<string, []>("op_2009"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2010_cast_fp16 = reshape(shape = var_2009, x = attn_weights_127_cast_fp16)[name = tensor<string, []>("op_2010_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_129_cast_fp16 = add(x = var_2010_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_129_cast_fp16")];
            tensor<int32, [3]> var_2015 = const()[name = tensor<string, []>("op_2015"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_341_cast_fp16 = reshape(shape = var_2015, x = attn_weights_129_cast_fp16)[name = tensor<string, []>("input_341_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_343_cast_fp16 = softmax(axis = var_5, x = input_341_cast_fp16)[name = tensor<string, []>("input_343_cast_fp16")];
            tensor<bool, []> attn_output_127_transpose_x_0 = const()[name = tensor<string, []>("attn_output_127_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_127_transpose_y_0 = const()[name = tensor<string, []>("attn_output_127_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_127_cast_fp16 = matmul(transpose_x = attn_output_127_transpose_x_0, transpose_y = attn_output_127_transpose_y_0, x = input_343_cast_fp16, y = value_states_87_cast_fp16)[name = tensor<string, []>("attn_output_127_cast_fp16")];
            tensor<int32, [4]> var_2020 = const()[name = tensor<string, []>("op_2020"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_129_cast_fp16 = reshape(shape = var_2020, x = attn_output_127_cast_fp16)[name = tensor<string, []>("attn_output_129_cast_fp16")];
            tensor<int32, [4]> attn_output_131_perm_0 = const()[name = tensor<string, []>("attn_output_131_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2023 = const()[name = tensor<string, []>("op_2023"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_131_cast_fp16 = transpose(perm = attn_output_131_perm_0, x = attn_output_129_cast_fp16)[name = tensor<string, []>("transpose_40")];
            tensor<fp16, [1, 77, 1280]> input_345_cast_fp16 = reshape(shape = var_2023, x = attn_output_131_cast_fp16)[name = tensor<string, []>("input_345_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(361613376))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(362842240))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(362842432)))];
            tensor<fp16, [1, 77, 1280]> linear_129_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16_palettized, x = input_345_cast_fp16)[name = tensor<string, []>("linear_129_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_347_cast_fp16 = add(x = input_339_cast_fp16, y = linear_129_cast_fp16)[name = tensor<string, []>("input_347_cast_fp16")];
            tensor<int32, [1]> input_349_axes_0 = const()[name = tensor<string, []>("input_349_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(362845056)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(362847680)))];
            tensor<fp16, [1, 77, 1280]> input_349_cast_fp16 = layer_norm(axes = input_349_axes_0, beta = text_encoder_text_model_encoder_layers_21_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_21_layer_norm2_weight_to_fp16, x = input_347_cast_fp16)[name = tensor<string, []>("input_349_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(362850304))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(367765568))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_21_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(367765760)))];
            tensor<fp16, [1, 77, 5120]> linear_130_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_21_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16_palettized, x = input_349_cast_fp16)[name = tensor<string, []>("linear_130_cast_fp16")];
            tensor<string, []> input_353_mode_0 = const()[name = tensor<string, []>("input_353_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_353_cast_fp16 = gelu(mode = input_353_mode_0, x = linear_130_cast_fp16)[name = tensor<string, []>("input_353_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_21_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(367776064))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(372691328))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(372691520)))];
            tensor<fp16, [1, 77, 1280]> linear_131_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_21_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_mlp_fc2_weight_to_fp16_palettized, x = input_353_cast_fp16)[name = tensor<string, []>("linear_131_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_355_cast_fp16 = add(x = input_347_cast_fp16, y = linear_131_cast_fp16)[name = tensor<string, []>("input_355_cast_fp16")];
            tensor<int32, [1]> hidden_states_133_axes_0 = const()[name = tensor<string, []>("hidden_states_133_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(372694144)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(372696768)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_133_cast_fp16 = layer_norm(axes = hidden_states_133_axes_0, beta = text_encoder_text_model_encoder_layers_22_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_22_layer_norm1_weight_to_fp16, x = input_355_cast_fp16)[name = tensor<string, []>("hidden_states_133_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(372699392))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(373928256))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(373928448)))];
            tensor<fp16, [1, 77, 1280]> linear_132_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_133_cast_fp16)[name = tensor<string, []>("linear_132_cast_fp16")];
            tensor<fp16, []> var_2062_to_fp16 = const()[name = tensor<string, []>("op_2062_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_137_cast_fp16 = mul(x = linear_132_cast_fp16, y = var_2062_to_fp16)[name = tensor<string, []>("tensor_137_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(373931072))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(375159936))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(375160128)))];
            tensor<fp16, [1, 77, 1280]> linear_133_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_133_cast_fp16)[name = tensor<string, []>("linear_133_cast_fp16")];
            tensor<int32, [4]> var_2067 = const()[name = tensor<string, []>("op_2067"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2068_cast_fp16 = reshape(shape = var_2067, x = linear_133_cast_fp16)[name = tensor<string, []>("op_2068_cast_fp16")];
            tensor<int32, [4]> var_2069_perm_0 = const()[name = tensor<string, []>("op_2069_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(375162752))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(376391616))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(376391808)))];
            tensor<fp16, [1, 77, 1280]> linear_134_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_133_cast_fp16)[name = tensor<string, []>("linear_134_cast_fp16")];
            tensor<int32, [4]> var_2074 = const()[name = tensor<string, []>("op_2074"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2075_cast_fp16 = reshape(shape = var_2074, x = linear_134_cast_fp16)[name = tensor<string, []>("op_2075_cast_fp16")];
            tensor<int32, [4]> var_2076_perm_0 = const()[name = tensor<string, []>("op_2076_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2083 = const()[name = tensor<string, []>("op_2083"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2084_cast_fp16 = reshape(shape = var_2083, x = tensor_137_cast_fp16)[name = tensor<string, []>("op_2084_cast_fp16")];
            tensor<int32, [4]> var_2085_perm_0 = const()[name = tensor<string, []>("op_2085_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2087 = const()[name = tensor<string, []>("op_2087"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2085_cast_fp16 = transpose(perm = var_2085_perm_0, x = var_2084_cast_fp16)[name = tensor<string, []>("transpose_39")];
            tensor<fp16, [20, 77, 64]> query_states_45_cast_fp16 = reshape(shape = var_2087, x = var_2085_cast_fp16)[name = tensor<string, []>("query_states_45_cast_fp16")];
            tensor<int32, [3]> var_2089 = const()[name = tensor<string, []>("op_2089"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2069_cast_fp16 = transpose(perm = var_2069_perm_0, x = var_2068_cast_fp16)[name = tensor<string, []>("transpose_38")];
            tensor<fp16, [20, 77, 64]> key_states_91_cast_fp16 = reshape(shape = var_2089, x = var_2069_cast_fp16)[name = tensor<string, []>("key_states_91_cast_fp16")];
            tensor<int32, [3]> var_2091 = const()[name = tensor<string, []>("op_2091"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2076_cast_fp16 = transpose(perm = var_2076_perm_0, x = var_2075_cast_fp16)[name = tensor<string, []>("transpose_37")];
            tensor<fp16, [20, 77, 64]> value_states_91_cast_fp16 = reshape(shape = var_2091, x = var_2076_cast_fp16)[name = tensor<string, []>("value_states_91_cast_fp16")];
            tensor<bool, []> attn_weights_133_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_133_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_133_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_133_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_133_cast_fp16 = matmul(transpose_x = attn_weights_133_transpose_x_1, transpose_y = attn_weights_133_transpose_y_1, x = query_states_45_cast_fp16, y = key_states_91_cast_fp16)[name = tensor<string, []>("attn_weights_133_cast_fp16")];
            tensor<int32, [4]> var_2096 = const()[name = tensor<string, []>("op_2096"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2097_cast_fp16 = reshape(shape = var_2096, x = attn_weights_133_cast_fp16)[name = tensor<string, []>("op_2097_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_135_cast_fp16 = add(x = var_2097_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_135_cast_fp16")];
            tensor<int32, [3]> var_2102 = const()[name = tensor<string, []>("op_2102"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_357_cast_fp16 = reshape(shape = var_2102, x = attn_weights_135_cast_fp16)[name = tensor<string, []>("input_357_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_359_cast_fp16 = softmax(axis = var_5, x = input_357_cast_fp16)[name = tensor<string, []>("input_359_cast_fp16")];
            tensor<bool, []> attn_output_133_transpose_x_0 = const()[name = tensor<string, []>("attn_output_133_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_133_transpose_y_0 = const()[name = tensor<string, []>("attn_output_133_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_133_cast_fp16 = matmul(transpose_x = attn_output_133_transpose_x_0, transpose_y = attn_output_133_transpose_y_0, x = input_359_cast_fp16, y = value_states_91_cast_fp16)[name = tensor<string, []>("attn_output_133_cast_fp16")];
            tensor<int32, [4]> var_2107 = const()[name = tensor<string, []>("op_2107"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_135_cast_fp16 = reshape(shape = var_2107, x = attn_output_133_cast_fp16)[name = tensor<string, []>("attn_output_135_cast_fp16")];
            tensor<int32, [4]> attn_output_137_perm_0 = const()[name = tensor<string, []>("attn_output_137_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2110 = const()[name = tensor<string, []>("op_2110"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_137_cast_fp16 = transpose(perm = attn_output_137_perm_0, x = attn_output_135_cast_fp16)[name = tensor<string, []>("transpose_36")];
            tensor<fp16, [1, 77, 1280]> input_361_cast_fp16 = reshape(shape = var_2110, x = attn_output_137_cast_fp16)[name = tensor<string, []>("input_361_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(376394432))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(377623296))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(377623488)))];
            tensor<fp16, [1, 77, 1280]> linear_135_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16_palettized, x = input_361_cast_fp16)[name = tensor<string, []>("linear_135_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_363_cast_fp16 = add(x = input_355_cast_fp16, y = linear_135_cast_fp16)[name = tensor<string, []>("input_363_cast_fp16")];
            tensor<int32, [1]> input_365_axes_0 = const()[name = tensor<string, []>("input_365_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(377626112)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(377628736)))];
            tensor<fp16, [1, 77, 1280]> input_365_cast_fp16 = layer_norm(axes = input_365_axes_0, beta = text_encoder_text_model_encoder_layers_22_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_22_layer_norm2_weight_to_fp16, x = input_363_cast_fp16)[name = tensor<string, []>("input_365_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(377631360))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(382546624))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_22_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(382546816)))];
            tensor<fp16, [1, 77, 5120]> linear_136_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_22_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16_palettized, x = input_365_cast_fp16)[name = tensor<string, []>("linear_136_cast_fp16")];
            tensor<string, []> input_369_mode_0 = const()[name = tensor<string, []>("input_369_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_369_cast_fp16 = gelu(mode = input_369_mode_0, x = linear_136_cast_fp16)[name = tensor<string, []>("input_369_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_22_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(382557120))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(387472384))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(387472576)))];
            tensor<fp16, [1, 77, 1280]> linear_137_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_22_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_mlp_fc2_weight_to_fp16_palettized, x = input_369_cast_fp16)[name = tensor<string, []>("linear_137_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_371_cast_fp16 = add(x = input_363_cast_fp16, y = linear_137_cast_fp16)[name = tensor<string, []>("input_371_cast_fp16")];
            tensor<int32, [1]> hidden_states_139_axes_0 = const()[name = tensor<string, []>("hidden_states_139_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(387475200)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(387477824)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_139_cast_fp16 = layer_norm(axes = hidden_states_139_axes_0, beta = text_encoder_text_model_encoder_layers_23_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_23_layer_norm1_weight_to_fp16, x = input_371_cast_fp16)[name = tensor<string, []>("hidden_states_139_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_23_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(387480448))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(388709312))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(388709504)))];
            tensor<fp16, [1, 77, 1280]> linear_138_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_23_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_139_cast_fp16)[name = tensor<string, []>("linear_138_cast_fp16")];
            tensor<fp16, []> var_2149_to_fp16 = const()[name = tensor<string, []>("op_2149_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_143_cast_fp16 = mul(x = linear_138_cast_fp16, y = var_2149_to_fp16)[name = tensor<string, []>("tensor_143_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_23_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(388712128))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(389940992))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(389941184)))];
            tensor<fp16, [1, 77, 1280]> linear_139_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_23_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_139_cast_fp16)[name = tensor<string, []>("linear_139_cast_fp16")];
            tensor<int32, [4]> var_2154 = const()[name = tensor<string, []>("op_2154"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2155_cast_fp16 = reshape(shape = var_2154, x = linear_139_cast_fp16)[name = tensor<string, []>("op_2155_cast_fp16")];
            tensor<int32, [4]> var_2156_perm_0 = const()[name = tensor<string, []>("op_2156_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_23_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(389943808))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(391172672))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(391172864)))];
            tensor<fp16, [1, 77, 1280]> linear_140_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_23_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_139_cast_fp16)[name = tensor<string, []>("linear_140_cast_fp16")];
            tensor<int32, [4]> var_2161 = const()[name = tensor<string, []>("op_2161"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2162_cast_fp16 = reshape(shape = var_2161, x = linear_140_cast_fp16)[name = tensor<string, []>("op_2162_cast_fp16")];
            tensor<int32, [4]> var_2163_perm_0 = const()[name = tensor<string, []>("op_2163_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2170 = const()[name = tensor<string, []>("op_2170"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2171_cast_fp16 = reshape(shape = var_2170, x = tensor_143_cast_fp16)[name = tensor<string, []>("op_2171_cast_fp16")];
            tensor<int32, [4]> var_2172_perm_0 = const()[name = tensor<string, []>("op_2172_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2174 = const()[name = tensor<string, []>("op_2174"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2172_cast_fp16 = transpose(perm = var_2172_perm_0, x = var_2171_cast_fp16)[name = tensor<string, []>("transpose_35")];
            tensor<fp16, [20, 77, 64]> query_states_47_cast_fp16 = reshape(shape = var_2174, x = var_2172_cast_fp16)[name = tensor<string, []>("query_states_47_cast_fp16")];
            tensor<int32, [3]> var_2176 = const()[name = tensor<string, []>("op_2176"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2156_cast_fp16 = transpose(perm = var_2156_perm_0, x = var_2155_cast_fp16)[name = tensor<string, []>("transpose_34")];
            tensor<fp16, [20, 77, 64]> key_states_95_cast_fp16 = reshape(shape = var_2176, x = var_2156_cast_fp16)[name = tensor<string, []>("key_states_95_cast_fp16")];
            tensor<int32, [3]> var_2178 = const()[name = tensor<string, []>("op_2178"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2163_cast_fp16 = transpose(perm = var_2163_perm_0, x = var_2162_cast_fp16)[name = tensor<string, []>("transpose_33")];
            tensor<fp16, [20, 77, 64]> value_states_95_cast_fp16 = reshape(shape = var_2178, x = var_2163_cast_fp16)[name = tensor<string, []>("value_states_95_cast_fp16")];
            tensor<bool, []> attn_weights_139_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_139_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_139_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_139_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_139_cast_fp16 = matmul(transpose_x = attn_weights_139_transpose_x_1, transpose_y = attn_weights_139_transpose_y_1, x = query_states_47_cast_fp16, y = key_states_95_cast_fp16)[name = tensor<string, []>("attn_weights_139_cast_fp16")];
            tensor<int32, [4]> var_2183 = const()[name = tensor<string, []>("op_2183"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2184_cast_fp16 = reshape(shape = var_2183, x = attn_weights_139_cast_fp16)[name = tensor<string, []>("op_2184_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_141_cast_fp16 = add(x = var_2184_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_141_cast_fp16")];
            tensor<int32, [3]> var_2189 = const()[name = tensor<string, []>("op_2189"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_373_cast_fp16 = reshape(shape = var_2189, x = attn_weights_141_cast_fp16)[name = tensor<string, []>("input_373_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_375_cast_fp16 = softmax(axis = var_5, x = input_373_cast_fp16)[name = tensor<string, []>("input_375_cast_fp16")];
            tensor<bool, []> attn_output_139_transpose_x_0 = const()[name = tensor<string, []>("attn_output_139_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_139_transpose_y_0 = const()[name = tensor<string, []>("attn_output_139_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_139_cast_fp16 = matmul(transpose_x = attn_output_139_transpose_x_0, transpose_y = attn_output_139_transpose_y_0, x = input_375_cast_fp16, y = value_states_95_cast_fp16)[name = tensor<string, []>("attn_output_139_cast_fp16")];
            tensor<int32, [4]> var_2194 = const()[name = tensor<string, []>("op_2194"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_141_cast_fp16 = reshape(shape = var_2194, x = attn_output_139_cast_fp16)[name = tensor<string, []>("attn_output_141_cast_fp16")];
            tensor<int32, [4]> attn_output_143_perm_0 = const()[name = tensor<string, []>("attn_output_143_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2197 = const()[name = tensor<string, []>("op_2197"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_143_cast_fp16 = transpose(perm = attn_output_143_perm_0, x = attn_output_141_cast_fp16)[name = tensor<string, []>("transpose_32")];
            tensor<fp16, [1, 77, 1280]> input_377_cast_fp16 = reshape(shape = var_2197, x = attn_output_143_cast_fp16)[name = tensor<string, []>("input_377_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_23_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(391175488))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(392404352))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(392404544)))];
            tensor<fp16, [1, 77, 1280]> linear_141_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_23_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_self_attn_out_proj_weight_to_fp16_palettized, x = input_377_cast_fp16)[name = tensor<string, []>("linear_141_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_379_cast_fp16 = add(x = input_371_cast_fp16, y = linear_141_cast_fp16)[name = tensor<string, []>("input_379_cast_fp16")];
            tensor<int32, [1]> input_381_axes_0 = const()[name = tensor<string, []>("input_381_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(392407168)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(392409792)))];
            tensor<fp16, [1, 77, 1280]> input_381_cast_fp16 = layer_norm(axes = input_381_axes_0, beta = text_encoder_text_model_encoder_layers_23_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_23_layer_norm2_weight_to_fp16, x = input_379_cast_fp16)[name = tensor<string, []>("input_381_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_23_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(392412416))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(397327680))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_23_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(397327872)))];
            tensor<fp16, [1, 77, 5120]> linear_142_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_23_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_mlp_fc1_weight_to_fp16_palettized, x = input_381_cast_fp16)[name = tensor<string, []>("linear_142_cast_fp16")];
            tensor<string, []> input_385_mode_0 = const()[name = tensor<string, []>("input_385_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_385_cast_fp16 = gelu(mode = input_385_mode_0, x = linear_142_cast_fp16)[name = tensor<string, []>("input_385_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_23_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(397338176))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(402253440))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(402253632)))];
            tensor<fp16, [1, 77, 1280]> linear_143_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_23_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_mlp_fc2_weight_to_fp16_palettized, x = input_385_cast_fp16)[name = tensor<string, []>("linear_143_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_387_cast_fp16 = add(x = input_379_cast_fp16, y = linear_143_cast_fp16)[name = tensor<string, []>("input_387_cast_fp16")];
            tensor<int32, [1]> hidden_states_145_axes_0 = const()[name = tensor<string, []>("hidden_states_145_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(402256256)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(402258880)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_145_cast_fp16 = layer_norm(axes = hidden_states_145_axes_0, beta = text_encoder_text_model_encoder_layers_24_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_24_layer_norm1_weight_to_fp16, x = input_387_cast_fp16)[name = tensor<string, []>("hidden_states_145_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_24_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(402261504))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(403490368))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(403490560)))];
            tensor<fp16, [1, 77, 1280]> linear_144_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_24_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_145_cast_fp16)[name = tensor<string, []>("linear_144_cast_fp16")];
            tensor<fp16, []> var_2236_to_fp16 = const()[name = tensor<string, []>("op_2236_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_149_cast_fp16 = mul(x = linear_144_cast_fp16, y = var_2236_to_fp16)[name = tensor<string, []>("tensor_149_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_24_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(403493184))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(404722048))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(404722240)))];
            tensor<fp16, [1, 77, 1280]> linear_145_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_24_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_145_cast_fp16)[name = tensor<string, []>("linear_145_cast_fp16")];
            tensor<int32, [4]> var_2241 = const()[name = tensor<string, []>("op_2241"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2242_cast_fp16 = reshape(shape = var_2241, x = linear_145_cast_fp16)[name = tensor<string, []>("op_2242_cast_fp16")];
            tensor<int32, [4]> var_2243_perm_0 = const()[name = tensor<string, []>("op_2243_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_24_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(404724864))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(405953728))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(405953920)))];
            tensor<fp16, [1, 77, 1280]> linear_146_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_24_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_145_cast_fp16)[name = tensor<string, []>("linear_146_cast_fp16")];
            tensor<int32, [4]> var_2248 = const()[name = tensor<string, []>("op_2248"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2249_cast_fp16 = reshape(shape = var_2248, x = linear_146_cast_fp16)[name = tensor<string, []>("op_2249_cast_fp16")];
            tensor<int32, [4]> var_2250_perm_0 = const()[name = tensor<string, []>("op_2250_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2257 = const()[name = tensor<string, []>("op_2257"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2258_cast_fp16 = reshape(shape = var_2257, x = tensor_149_cast_fp16)[name = tensor<string, []>("op_2258_cast_fp16")];
            tensor<int32, [4]> var_2259_perm_0 = const()[name = tensor<string, []>("op_2259_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2261 = const()[name = tensor<string, []>("op_2261"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2259_cast_fp16 = transpose(perm = var_2259_perm_0, x = var_2258_cast_fp16)[name = tensor<string, []>("transpose_31")];
            tensor<fp16, [20, 77, 64]> query_states_49_cast_fp16 = reshape(shape = var_2261, x = var_2259_cast_fp16)[name = tensor<string, []>("query_states_49_cast_fp16")];
            tensor<int32, [3]> var_2263 = const()[name = tensor<string, []>("op_2263"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2243_cast_fp16 = transpose(perm = var_2243_perm_0, x = var_2242_cast_fp16)[name = tensor<string, []>("transpose_30")];
            tensor<fp16, [20, 77, 64]> key_states_99_cast_fp16 = reshape(shape = var_2263, x = var_2243_cast_fp16)[name = tensor<string, []>("key_states_99_cast_fp16")];
            tensor<int32, [3]> var_2265 = const()[name = tensor<string, []>("op_2265"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2250_cast_fp16 = transpose(perm = var_2250_perm_0, x = var_2249_cast_fp16)[name = tensor<string, []>("transpose_29")];
            tensor<fp16, [20, 77, 64]> value_states_99_cast_fp16 = reshape(shape = var_2265, x = var_2250_cast_fp16)[name = tensor<string, []>("value_states_99_cast_fp16")];
            tensor<bool, []> attn_weights_145_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_145_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_145_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_145_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_145_cast_fp16 = matmul(transpose_x = attn_weights_145_transpose_x_1, transpose_y = attn_weights_145_transpose_y_1, x = query_states_49_cast_fp16, y = key_states_99_cast_fp16)[name = tensor<string, []>("attn_weights_145_cast_fp16")];
            tensor<int32, [4]> var_2270 = const()[name = tensor<string, []>("op_2270"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2271_cast_fp16 = reshape(shape = var_2270, x = attn_weights_145_cast_fp16)[name = tensor<string, []>("op_2271_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_147_cast_fp16 = add(x = var_2271_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_147_cast_fp16")];
            tensor<int32, [3]> var_2276 = const()[name = tensor<string, []>("op_2276"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_389_cast_fp16 = reshape(shape = var_2276, x = attn_weights_147_cast_fp16)[name = tensor<string, []>("input_389_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_391_cast_fp16 = softmax(axis = var_5, x = input_389_cast_fp16)[name = tensor<string, []>("input_391_cast_fp16")];
            tensor<bool, []> attn_output_145_transpose_x_0 = const()[name = tensor<string, []>("attn_output_145_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_145_transpose_y_0 = const()[name = tensor<string, []>("attn_output_145_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_145_cast_fp16 = matmul(transpose_x = attn_output_145_transpose_x_0, transpose_y = attn_output_145_transpose_y_0, x = input_391_cast_fp16, y = value_states_99_cast_fp16)[name = tensor<string, []>("attn_output_145_cast_fp16")];
            tensor<int32, [4]> var_2281 = const()[name = tensor<string, []>("op_2281"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_147_cast_fp16 = reshape(shape = var_2281, x = attn_output_145_cast_fp16)[name = tensor<string, []>("attn_output_147_cast_fp16")];
            tensor<int32, [4]> attn_output_149_perm_0 = const()[name = tensor<string, []>("attn_output_149_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2284 = const()[name = tensor<string, []>("op_2284"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_149_cast_fp16 = transpose(perm = attn_output_149_perm_0, x = attn_output_147_cast_fp16)[name = tensor<string, []>("transpose_28")];
            tensor<fp16, [1, 77, 1280]> input_393_cast_fp16 = reshape(shape = var_2284, x = attn_output_149_cast_fp16)[name = tensor<string, []>("input_393_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_24_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(405956544))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(407185408))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(407185600)))];
            tensor<fp16, [1, 77, 1280]> linear_147_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_24_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_self_attn_out_proj_weight_to_fp16_palettized, x = input_393_cast_fp16)[name = tensor<string, []>("linear_147_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_395_cast_fp16 = add(x = input_387_cast_fp16, y = linear_147_cast_fp16)[name = tensor<string, []>("input_395_cast_fp16")];
            tensor<int32, [1]> input_397_axes_0 = const()[name = tensor<string, []>("input_397_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(407188224)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(407190848)))];
            tensor<fp16, [1, 77, 1280]> input_397_cast_fp16 = layer_norm(axes = input_397_axes_0, beta = text_encoder_text_model_encoder_layers_24_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_24_layer_norm2_weight_to_fp16, x = input_395_cast_fp16)[name = tensor<string, []>("input_397_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_24_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(407193472))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(412108736))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_24_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(412108928)))];
            tensor<fp16, [1, 77, 5120]> linear_148_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_24_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_mlp_fc1_weight_to_fp16_palettized, x = input_397_cast_fp16)[name = tensor<string, []>("linear_148_cast_fp16")];
            tensor<string, []> input_401_mode_0 = const()[name = tensor<string, []>("input_401_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_401_cast_fp16 = gelu(mode = input_401_mode_0, x = linear_148_cast_fp16)[name = tensor<string, []>("input_401_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_24_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(412119232))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(417034496))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(417034688)))];
            tensor<fp16, [1, 77, 1280]> linear_149_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_24_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_mlp_fc2_weight_to_fp16_palettized, x = input_401_cast_fp16)[name = tensor<string, []>("linear_149_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_403_cast_fp16 = add(x = input_395_cast_fp16, y = linear_149_cast_fp16)[name = tensor<string, []>("input_403_cast_fp16")];
            tensor<int32, [1]> hidden_states_151_axes_0 = const()[name = tensor<string, []>("hidden_states_151_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(417037312)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(417039936)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_151_cast_fp16 = layer_norm(axes = hidden_states_151_axes_0, beta = text_encoder_text_model_encoder_layers_25_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_25_layer_norm1_weight_to_fp16, x = input_403_cast_fp16)[name = tensor<string, []>("hidden_states_151_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_25_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(417042560))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(418271424))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(418271616)))];
            tensor<fp16, [1, 77, 1280]> linear_150_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_25_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_151_cast_fp16)[name = tensor<string, []>("linear_150_cast_fp16")];
            tensor<fp16, []> var_2323_to_fp16 = const()[name = tensor<string, []>("op_2323_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_155_cast_fp16 = mul(x = linear_150_cast_fp16, y = var_2323_to_fp16)[name = tensor<string, []>("tensor_155_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_25_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(418274240))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(419503104))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(419503296)))];
            tensor<fp16, [1, 77, 1280]> linear_151_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_25_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_151_cast_fp16)[name = tensor<string, []>("linear_151_cast_fp16")];
            tensor<int32, [4]> var_2328 = const()[name = tensor<string, []>("op_2328"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2329_cast_fp16 = reshape(shape = var_2328, x = linear_151_cast_fp16)[name = tensor<string, []>("op_2329_cast_fp16")];
            tensor<int32, [4]> var_2330_perm_0 = const()[name = tensor<string, []>("op_2330_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_25_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(419505920))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(420734784))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(420734976)))];
            tensor<fp16, [1, 77, 1280]> linear_152_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_25_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_151_cast_fp16)[name = tensor<string, []>("linear_152_cast_fp16")];
            tensor<int32, [4]> var_2335 = const()[name = tensor<string, []>("op_2335"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2336_cast_fp16 = reshape(shape = var_2335, x = linear_152_cast_fp16)[name = tensor<string, []>("op_2336_cast_fp16")];
            tensor<int32, [4]> var_2337_perm_0 = const()[name = tensor<string, []>("op_2337_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2344 = const()[name = tensor<string, []>("op_2344"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2345_cast_fp16 = reshape(shape = var_2344, x = tensor_155_cast_fp16)[name = tensor<string, []>("op_2345_cast_fp16")];
            tensor<int32, [4]> var_2346_perm_0 = const()[name = tensor<string, []>("op_2346_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2348 = const()[name = tensor<string, []>("op_2348"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2346_cast_fp16 = transpose(perm = var_2346_perm_0, x = var_2345_cast_fp16)[name = tensor<string, []>("transpose_27")];
            tensor<fp16, [20, 77, 64]> query_states_51_cast_fp16 = reshape(shape = var_2348, x = var_2346_cast_fp16)[name = tensor<string, []>("query_states_51_cast_fp16")];
            tensor<int32, [3]> var_2350 = const()[name = tensor<string, []>("op_2350"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2330_cast_fp16 = transpose(perm = var_2330_perm_0, x = var_2329_cast_fp16)[name = tensor<string, []>("transpose_26")];
            tensor<fp16, [20, 77, 64]> key_states_103_cast_fp16 = reshape(shape = var_2350, x = var_2330_cast_fp16)[name = tensor<string, []>("key_states_103_cast_fp16")];
            tensor<int32, [3]> var_2352 = const()[name = tensor<string, []>("op_2352"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2337_cast_fp16 = transpose(perm = var_2337_perm_0, x = var_2336_cast_fp16)[name = tensor<string, []>("transpose_25")];
            tensor<fp16, [20, 77, 64]> value_states_103_cast_fp16 = reshape(shape = var_2352, x = var_2337_cast_fp16)[name = tensor<string, []>("value_states_103_cast_fp16")];
            tensor<bool, []> attn_weights_151_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_151_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_151_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_151_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_151_cast_fp16 = matmul(transpose_x = attn_weights_151_transpose_x_1, transpose_y = attn_weights_151_transpose_y_1, x = query_states_51_cast_fp16, y = key_states_103_cast_fp16)[name = tensor<string, []>("attn_weights_151_cast_fp16")];
            tensor<int32, [4]> var_2357 = const()[name = tensor<string, []>("op_2357"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2358_cast_fp16 = reshape(shape = var_2357, x = attn_weights_151_cast_fp16)[name = tensor<string, []>("op_2358_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_153_cast_fp16 = add(x = var_2358_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_153_cast_fp16")];
            tensor<int32, [3]> var_2363 = const()[name = tensor<string, []>("op_2363"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_405_cast_fp16 = reshape(shape = var_2363, x = attn_weights_153_cast_fp16)[name = tensor<string, []>("input_405_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_407_cast_fp16 = softmax(axis = var_5, x = input_405_cast_fp16)[name = tensor<string, []>("input_407_cast_fp16")];
            tensor<bool, []> attn_output_151_transpose_x_0 = const()[name = tensor<string, []>("attn_output_151_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_151_transpose_y_0 = const()[name = tensor<string, []>("attn_output_151_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_151_cast_fp16 = matmul(transpose_x = attn_output_151_transpose_x_0, transpose_y = attn_output_151_transpose_y_0, x = input_407_cast_fp16, y = value_states_103_cast_fp16)[name = tensor<string, []>("attn_output_151_cast_fp16")];
            tensor<int32, [4]> var_2368 = const()[name = tensor<string, []>("op_2368"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_153_cast_fp16 = reshape(shape = var_2368, x = attn_output_151_cast_fp16)[name = tensor<string, []>("attn_output_153_cast_fp16")];
            tensor<int32, [4]> attn_output_155_perm_0 = const()[name = tensor<string, []>("attn_output_155_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2371 = const()[name = tensor<string, []>("op_2371"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_155_cast_fp16 = transpose(perm = attn_output_155_perm_0, x = attn_output_153_cast_fp16)[name = tensor<string, []>("transpose_24")];
            tensor<fp16, [1, 77, 1280]> input_409_cast_fp16 = reshape(shape = var_2371, x = attn_output_155_cast_fp16)[name = tensor<string, []>("input_409_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_25_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(420737600))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(421966464))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(421966656)))];
            tensor<fp16, [1, 77, 1280]> linear_153_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_25_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_self_attn_out_proj_weight_to_fp16_palettized, x = input_409_cast_fp16)[name = tensor<string, []>("linear_153_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_411_cast_fp16 = add(x = input_403_cast_fp16, y = linear_153_cast_fp16)[name = tensor<string, []>("input_411_cast_fp16")];
            tensor<int32, [1]> input_413_axes_0 = const()[name = tensor<string, []>("input_413_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(421969280)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(421971904)))];
            tensor<fp16, [1, 77, 1280]> input_413_cast_fp16 = layer_norm(axes = input_413_axes_0, beta = text_encoder_text_model_encoder_layers_25_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_25_layer_norm2_weight_to_fp16, x = input_411_cast_fp16)[name = tensor<string, []>("input_413_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_25_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(421974528))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(426889792))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_25_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(426889984)))];
            tensor<fp16, [1, 77, 5120]> linear_154_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_25_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_mlp_fc1_weight_to_fp16_palettized, x = input_413_cast_fp16)[name = tensor<string, []>("linear_154_cast_fp16")];
            tensor<string, []> input_417_mode_0 = const()[name = tensor<string, []>("input_417_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_417_cast_fp16 = gelu(mode = input_417_mode_0, x = linear_154_cast_fp16)[name = tensor<string, []>("input_417_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_25_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(426900288))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(431815552))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(431815744)))];
            tensor<fp16, [1, 77, 1280]> linear_155_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_25_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_mlp_fc2_weight_to_fp16_palettized, x = input_417_cast_fp16)[name = tensor<string, []>("linear_155_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_419_cast_fp16 = add(x = input_411_cast_fp16, y = linear_155_cast_fp16)[name = tensor<string, []>("input_419_cast_fp16")];
            tensor<int32, [1]> hidden_states_157_axes_0 = const()[name = tensor<string, []>("hidden_states_157_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(431818368)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(431820992)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_157_cast_fp16 = layer_norm(axes = hidden_states_157_axes_0, beta = text_encoder_text_model_encoder_layers_26_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_26_layer_norm1_weight_to_fp16, x = input_419_cast_fp16)[name = tensor<string, []>("hidden_states_157_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_26_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(431823616))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(433052480))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(433052672)))];
            tensor<fp16, [1, 77, 1280]> linear_156_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_26_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_157_cast_fp16)[name = tensor<string, []>("linear_156_cast_fp16")];
            tensor<fp16, []> var_2410_to_fp16 = const()[name = tensor<string, []>("op_2410_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_161_cast_fp16 = mul(x = linear_156_cast_fp16, y = var_2410_to_fp16)[name = tensor<string, []>("tensor_161_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_26_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(433055296))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(434284160))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(434284352)))];
            tensor<fp16, [1, 77, 1280]> linear_157_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_26_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_157_cast_fp16)[name = tensor<string, []>("linear_157_cast_fp16")];
            tensor<int32, [4]> var_2415 = const()[name = tensor<string, []>("op_2415"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2416_cast_fp16 = reshape(shape = var_2415, x = linear_157_cast_fp16)[name = tensor<string, []>("op_2416_cast_fp16")];
            tensor<int32, [4]> var_2417_perm_0 = const()[name = tensor<string, []>("op_2417_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_26_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(434286976))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(435515840))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(435516032)))];
            tensor<fp16, [1, 77, 1280]> linear_158_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_26_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_157_cast_fp16)[name = tensor<string, []>("linear_158_cast_fp16")];
            tensor<int32, [4]> var_2422 = const()[name = tensor<string, []>("op_2422"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2423_cast_fp16 = reshape(shape = var_2422, x = linear_158_cast_fp16)[name = tensor<string, []>("op_2423_cast_fp16")];
            tensor<int32, [4]> var_2424_perm_0 = const()[name = tensor<string, []>("op_2424_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2431 = const()[name = tensor<string, []>("op_2431"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2432_cast_fp16 = reshape(shape = var_2431, x = tensor_161_cast_fp16)[name = tensor<string, []>("op_2432_cast_fp16")];
            tensor<int32, [4]> var_2433_perm_0 = const()[name = tensor<string, []>("op_2433_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2435 = const()[name = tensor<string, []>("op_2435"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2433_cast_fp16 = transpose(perm = var_2433_perm_0, x = var_2432_cast_fp16)[name = tensor<string, []>("transpose_23")];
            tensor<fp16, [20, 77, 64]> query_states_53_cast_fp16 = reshape(shape = var_2435, x = var_2433_cast_fp16)[name = tensor<string, []>("query_states_53_cast_fp16")];
            tensor<int32, [3]> var_2437 = const()[name = tensor<string, []>("op_2437"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2417_cast_fp16 = transpose(perm = var_2417_perm_0, x = var_2416_cast_fp16)[name = tensor<string, []>("transpose_22")];
            tensor<fp16, [20, 77, 64]> key_states_107_cast_fp16 = reshape(shape = var_2437, x = var_2417_cast_fp16)[name = tensor<string, []>("key_states_107_cast_fp16")];
            tensor<int32, [3]> var_2439 = const()[name = tensor<string, []>("op_2439"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2424_cast_fp16 = transpose(perm = var_2424_perm_0, x = var_2423_cast_fp16)[name = tensor<string, []>("transpose_21")];
            tensor<fp16, [20, 77, 64]> value_states_107_cast_fp16 = reshape(shape = var_2439, x = var_2424_cast_fp16)[name = tensor<string, []>("value_states_107_cast_fp16")];
            tensor<bool, []> attn_weights_157_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_157_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_157_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_157_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_157_cast_fp16 = matmul(transpose_x = attn_weights_157_transpose_x_1, transpose_y = attn_weights_157_transpose_y_1, x = query_states_53_cast_fp16, y = key_states_107_cast_fp16)[name = tensor<string, []>("attn_weights_157_cast_fp16")];
            tensor<int32, [4]> var_2444 = const()[name = tensor<string, []>("op_2444"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2445_cast_fp16 = reshape(shape = var_2444, x = attn_weights_157_cast_fp16)[name = tensor<string, []>("op_2445_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_159_cast_fp16 = add(x = var_2445_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_159_cast_fp16")];
            tensor<int32, [3]> var_2450 = const()[name = tensor<string, []>("op_2450"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_421_cast_fp16 = reshape(shape = var_2450, x = attn_weights_159_cast_fp16)[name = tensor<string, []>("input_421_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_423_cast_fp16 = softmax(axis = var_5, x = input_421_cast_fp16)[name = tensor<string, []>("input_423_cast_fp16")];
            tensor<bool, []> attn_output_157_transpose_x_0 = const()[name = tensor<string, []>("attn_output_157_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_157_transpose_y_0 = const()[name = tensor<string, []>("attn_output_157_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_157_cast_fp16 = matmul(transpose_x = attn_output_157_transpose_x_0, transpose_y = attn_output_157_transpose_y_0, x = input_423_cast_fp16, y = value_states_107_cast_fp16)[name = tensor<string, []>("attn_output_157_cast_fp16")];
            tensor<int32, [4]> var_2455 = const()[name = tensor<string, []>("op_2455"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_159_cast_fp16 = reshape(shape = var_2455, x = attn_output_157_cast_fp16)[name = tensor<string, []>("attn_output_159_cast_fp16")];
            tensor<int32, [4]> attn_output_161_perm_0 = const()[name = tensor<string, []>("attn_output_161_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2458 = const()[name = tensor<string, []>("op_2458"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_161_cast_fp16 = transpose(perm = attn_output_161_perm_0, x = attn_output_159_cast_fp16)[name = tensor<string, []>("transpose_20")];
            tensor<fp16, [1, 77, 1280]> input_425_cast_fp16 = reshape(shape = var_2458, x = attn_output_161_cast_fp16)[name = tensor<string, []>("input_425_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_26_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(435518656))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(436747520))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(436747712)))];
            tensor<fp16, [1, 77, 1280]> linear_159_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_26_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_self_attn_out_proj_weight_to_fp16_palettized, x = input_425_cast_fp16)[name = tensor<string, []>("linear_159_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_427_cast_fp16 = add(x = input_419_cast_fp16, y = linear_159_cast_fp16)[name = tensor<string, []>("input_427_cast_fp16")];
            tensor<int32, [1]> input_429_axes_0 = const()[name = tensor<string, []>("input_429_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(436750336)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(436752960)))];
            tensor<fp16, [1, 77, 1280]> input_429_cast_fp16 = layer_norm(axes = input_429_axes_0, beta = text_encoder_text_model_encoder_layers_26_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_26_layer_norm2_weight_to_fp16, x = input_427_cast_fp16)[name = tensor<string, []>("input_429_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_26_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(436755584))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441670848))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_26_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441671040)))];
            tensor<fp16, [1, 77, 5120]> linear_160_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_26_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_mlp_fc1_weight_to_fp16_palettized, x = input_429_cast_fp16)[name = tensor<string, []>("linear_160_cast_fp16")];
            tensor<string, []> input_433_mode_0 = const()[name = tensor<string, []>("input_433_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_433_cast_fp16 = gelu(mode = input_433_mode_0, x = linear_160_cast_fp16)[name = tensor<string, []>("input_433_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_26_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441681344))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(446596608))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(446596800)))];
            tensor<fp16, [1, 77, 1280]> linear_161_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_26_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_mlp_fc2_weight_to_fp16_palettized, x = input_433_cast_fp16)[name = tensor<string, []>("linear_161_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_435_cast_fp16 = add(x = input_427_cast_fp16, y = linear_161_cast_fp16)[name = tensor<string, []>("input_435_cast_fp16")];
            tensor<int32, [1]> hidden_states_163_axes_0 = const()[name = tensor<string, []>("hidden_states_163_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(446599424)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(446602048)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_163_cast_fp16 = layer_norm(axes = hidden_states_163_axes_0, beta = text_encoder_text_model_encoder_layers_27_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_27_layer_norm1_weight_to_fp16, x = input_435_cast_fp16)[name = tensor<string, []>("hidden_states_163_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_27_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(446604672))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(447833536))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(447833728)))];
            tensor<fp16, [1, 77, 1280]> linear_162_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_27_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_163_cast_fp16)[name = tensor<string, []>("linear_162_cast_fp16")];
            tensor<fp16, []> var_2497_to_fp16 = const()[name = tensor<string, []>("op_2497_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_167_cast_fp16 = mul(x = linear_162_cast_fp16, y = var_2497_to_fp16)[name = tensor<string, []>("tensor_167_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_27_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(447836352))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(449065216))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(449065408)))];
            tensor<fp16, [1, 77, 1280]> linear_163_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_27_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_163_cast_fp16)[name = tensor<string, []>("linear_163_cast_fp16")];
            tensor<int32, [4]> var_2502 = const()[name = tensor<string, []>("op_2502"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2503_cast_fp16 = reshape(shape = var_2502, x = linear_163_cast_fp16)[name = tensor<string, []>("op_2503_cast_fp16")];
            tensor<int32, [4]> var_2504_perm_0 = const()[name = tensor<string, []>("op_2504_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_27_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(449068032))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(450296896))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(450297088)))];
            tensor<fp16, [1, 77, 1280]> linear_164_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_27_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_163_cast_fp16)[name = tensor<string, []>("linear_164_cast_fp16")];
            tensor<int32, [4]> var_2509 = const()[name = tensor<string, []>("op_2509"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2510_cast_fp16 = reshape(shape = var_2509, x = linear_164_cast_fp16)[name = tensor<string, []>("op_2510_cast_fp16")];
            tensor<int32, [4]> var_2511_perm_0 = const()[name = tensor<string, []>("op_2511_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2518 = const()[name = tensor<string, []>("op_2518"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2519_cast_fp16 = reshape(shape = var_2518, x = tensor_167_cast_fp16)[name = tensor<string, []>("op_2519_cast_fp16")];
            tensor<int32, [4]> var_2520_perm_0 = const()[name = tensor<string, []>("op_2520_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2522 = const()[name = tensor<string, []>("op_2522"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2520_cast_fp16 = transpose(perm = var_2520_perm_0, x = var_2519_cast_fp16)[name = tensor<string, []>("transpose_19")];
            tensor<fp16, [20, 77, 64]> query_states_55_cast_fp16 = reshape(shape = var_2522, x = var_2520_cast_fp16)[name = tensor<string, []>("query_states_55_cast_fp16")];
            tensor<int32, [3]> var_2524 = const()[name = tensor<string, []>("op_2524"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2504_cast_fp16 = transpose(perm = var_2504_perm_0, x = var_2503_cast_fp16)[name = tensor<string, []>("transpose_18")];
            tensor<fp16, [20, 77, 64]> key_states_111_cast_fp16 = reshape(shape = var_2524, x = var_2504_cast_fp16)[name = tensor<string, []>("key_states_111_cast_fp16")];
            tensor<int32, [3]> var_2526 = const()[name = tensor<string, []>("op_2526"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2511_cast_fp16 = transpose(perm = var_2511_perm_0, x = var_2510_cast_fp16)[name = tensor<string, []>("transpose_17")];
            tensor<fp16, [20, 77, 64]> value_states_111_cast_fp16 = reshape(shape = var_2526, x = var_2511_cast_fp16)[name = tensor<string, []>("value_states_111_cast_fp16")];
            tensor<bool, []> attn_weights_163_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_163_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_163_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_163_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_163_cast_fp16 = matmul(transpose_x = attn_weights_163_transpose_x_1, transpose_y = attn_weights_163_transpose_y_1, x = query_states_55_cast_fp16, y = key_states_111_cast_fp16)[name = tensor<string, []>("attn_weights_163_cast_fp16")];
            tensor<int32, [4]> var_2531 = const()[name = tensor<string, []>("op_2531"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2532_cast_fp16 = reshape(shape = var_2531, x = attn_weights_163_cast_fp16)[name = tensor<string, []>("op_2532_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_165_cast_fp16 = add(x = var_2532_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_165_cast_fp16")];
            tensor<int32, [3]> var_2537 = const()[name = tensor<string, []>("op_2537"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_437_cast_fp16 = reshape(shape = var_2537, x = attn_weights_165_cast_fp16)[name = tensor<string, []>("input_437_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_439_cast_fp16 = softmax(axis = var_5, x = input_437_cast_fp16)[name = tensor<string, []>("input_439_cast_fp16")];
            tensor<bool, []> attn_output_163_transpose_x_0 = const()[name = tensor<string, []>("attn_output_163_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_163_transpose_y_0 = const()[name = tensor<string, []>("attn_output_163_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_163_cast_fp16 = matmul(transpose_x = attn_output_163_transpose_x_0, transpose_y = attn_output_163_transpose_y_0, x = input_439_cast_fp16, y = value_states_111_cast_fp16)[name = tensor<string, []>("attn_output_163_cast_fp16")];
            tensor<int32, [4]> var_2542 = const()[name = tensor<string, []>("op_2542"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_165_cast_fp16 = reshape(shape = var_2542, x = attn_output_163_cast_fp16)[name = tensor<string, []>("attn_output_165_cast_fp16")];
            tensor<int32, [4]> attn_output_167_perm_0 = const()[name = tensor<string, []>("attn_output_167_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2545 = const()[name = tensor<string, []>("op_2545"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_167_cast_fp16 = transpose(perm = attn_output_167_perm_0, x = attn_output_165_cast_fp16)[name = tensor<string, []>("transpose_16")];
            tensor<fp16, [1, 77, 1280]> input_441_cast_fp16 = reshape(shape = var_2545, x = attn_output_167_cast_fp16)[name = tensor<string, []>("input_441_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_27_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(450299712))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(451528576))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(451528768)))];
            tensor<fp16, [1, 77, 1280]> linear_165_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_27_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_self_attn_out_proj_weight_to_fp16_palettized, x = input_441_cast_fp16)[name = tensor<string, []>("linear_165_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_443_cast_fp16 = add(x = input_435_cast_fp16, y = linear_165_cast_fp16)[name = tensor<string, []>("input_443_cast_fp16")];
            tensor<int32, [1]> input_445_axes_0 = const()[name = tensor<string, []>("input_445_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(451531392)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(451534016)))];
            tensor<fp16, [1, 77, 1280]> input_445_cast_fp16 = layer_norm(axes = input_445_axes_0, beta = text_encoder_text_model_encoder_layers_27_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_27_layer_norm2_weight_to_fp16, x = input_443_cast_fp16)[name = tensor<string, []>("input_445_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_27_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(451536640))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(456451904))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_27_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(456452096)))];
            tensor<fp16, [1, 77, 5120]> linear_166_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_27_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_mlp_fc1_weight_to_fp16_palettized, x = input_445_cast_fp16)[name = tensor<string, []>("linear_166_cast_fp16")];
            tensor<string, []> input_449_mode_0 = const()[name = tensor<string, []>("input_449_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_449_cast_fp16 = gelu(mode = input_449_mode_0, x = linear_166_cast_fp16)[name = tensor<string, []>("input_449_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_27_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(456462400))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(461377664))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(461377856)))];
            tensor<fp16, [1, 77, 1280]> linear_167_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_27_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_mlp_fc2_weight_to_fp16_palettized, x = input_449_cast_fp16)[name = tensor<string, []>("linear_167_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_451_cast_fp16 = add(x = input_443_cast_fp16, y = linear_167_cast_fp16)[name = tensor<string, []>("input_451_cast_fp16")];
            tensor<int32, [1]> hidden_states_169_axes_0 = const()[name = tensor<string, []>("hidden_states_169_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(461380480)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(461383104)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_169_cast_fp16 = layer_norm(axes = hidden_states_169_axes_0, beta = text_encoder_text_model_encoder_layers_28_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_28_layer_norm1_weight_to_fp16, x = input_451_cast_fp16)[name = tensor<string, []>("hidden_states_169_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_28_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(461385728))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(462614592))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(462614784)))];
            tensor<fp16, [1, 77, 1280]> linear_168_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_28_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_169_cast_fp16)[name = tensor<string, []>("linear_168_cast_fp16")];
            tensor<fp16, []> var_2584_to_fp16 = const()[name = tensor<string, []>("op_2584_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_173_cast_fp16 = mul(x = linear_168_cast_fp16, y = var_2584_to_fp16)[name = tensor<string, []>("tensor_173_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_28_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(462617408))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(463846272))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(463846464)))];
            tensor<fp16, [1, 77, 1280]> linear_169_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_28_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_169_cast_fp16)[name = tensor<string, []>("linear_169_cast_fp16")];
            tensor<int32, [4]> var_2589 = const()[name = tensor<string, []>("op_2589"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2590_cast_fp16 = reshape(shape = var_2589, x = linear_169_cast_fp16)[name = tensor<string, []>("op_2590_cast_fp16")];
            tensor<int32, [4]> var_2591_perm_0 = const()[name = tensor<string, []>("op_2591_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_28_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(463849088))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(465077952))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(465078144)))];
            tensor<fp16, [1, 77, 1280]> linear_170_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_28_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_169_cast_fp16)[name = tensor<string, []>("linear_170_cast_fp16")];
            tensor<int32, [4]> var_2596 = const()[name = tensor<string, []>("op_2596"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2597_cast_fp16 = reshape(shape = var_2596, x = linear_170_cast_fp16)[name = tensor<string, []>("op_2597_cast_fp16")];
            tensor<int32, [4]> var_2598_perm_0 = const()[name = tensor<string, []>("op_2598_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2605 = const()[name = tensor<string, []>("op_2605"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2606_cast_fp16 = reshape(shape = var_2605, x = tensor_173_cast_fp16)[name = tensor<string, []>("op_2606_cast_fp16")];
            tensor<int32, [4]> var_2607_perm_0 = const()[name = tensor<string, []>("op_2607_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2609 = const()[name = tensor<string, []>("op_2609"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2607_cast_fp16 = transpose(perm = var_2607_perm_0, x = var_2606_cast_fp16)[name = tensor<string, []>("transpose_15")];
            tensor<fp16, [20, 77, 64]> query_states_57_cast_fp16 = reshape(shape = var_2609, x = var_2607_cast_fp16)[name = tensor<string, []>("query_states_57_cast_fp16")];
            tensor<int32, [3]> var_2611 = const()[name = tensor<string, []>("op_2611"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2591_cast_fp16 = transpose(perm = var_2591_perm_0, x = var_2590_cast_fp16)[name = tensor<string, []>("transpose_14")];
            tensor<fp16, [20, 77, 64]> key_states_115_cast_fp16 = reshape(shape = var_2611, x = var_2591_cast_fp16)[name = tensor<string, []>("key_states_115_cast_fp16")];
            tensor<int32, [3]> var_2613 = const()[name = tensor<string, []>("op_2613"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2598_cast_fp16 = transpose(perm = var_2598_perm_0, x = var_2597_cast_fp16)[name = tensor<string, []>("transpose_13")];
            tensor<fp16, [20, 77, 64]> value_states_115_cast_fp16 = reshape(shape = var_2613, x = var_2598_cast_fp16)[name = tensor<string, []>("value_states_115_cast_fp16")];
            tensor<bool, []> attn_weights_169_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_169_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_169_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_169_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_169_cast_fp16 = matmul(transpose_x = attn_weights_169_transpose_x_1, transpose_y = attn_weights_169_transpose_y_1, x = query_states_57_cast_fp16, y = key_states_115_cast_fp16)[name = tensor<string, []>("attn_weights_169_cast_fp16")];
            tensor<int32, [4]> var_2618 = const()[name = tensor<string, []>("op_2618"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2619_cast_fp16 = reshape(shape = var_2618, x = attn_weights_169_cast_fp16)[name = tensor<string, []>("op_2619_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_171_cast_fp16 = add(x = var_2619_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_171_cast_fp16")];
            tensor<int32, [3]> var_2624 = const()[name = tensor<string, []>("op_2624"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_453_cast_fp16 = reshape(shape = var_2624, x = attn_weights_171_cast_fp16)[name = tensor<string, []>("input_453_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_455_cast_fp16 = softmax(axis = var_5, x = input_453_cast_fp16)[name = tensor<string, []>("input_455_cast_fp16")];
            tensor<bool, []> attn_output_169_transpose_x_0 = const()[name = tensor<string, []>("attn_output_169_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_169_transpose_y_0 = const()[name = tensor<string, []>("attn_output_169_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_169_cast_fp16 = matmul(transpose_x = attn_output_169_transpose_x_0, transpose_y = attn_output_169_transpose_y_0, x = input_455_cast_fp16, y = value_states_115_cast_fp16)[name = tensor<string, []>("attn_output_169_cast_fp16")];
            tensor<int32, [4]> var_2629 = const()[name = tensor<string, []>("op_2629"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_171_cast_fp16 = reshape(shape = var_2629, x = attn_output_169_cast_fp16)[name = tensor<string, []>("attn_output_171_cast_fp16")];
            tensor<int32, [4]> attn_output_173_perm_0 = const()[name = tensor<string, []>("attn_output_173_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2632 = const()[name = tensor<string, []>("op_2632"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_173_cast_fp16 = transpose(perm = attn_output_173_perm_0, x = attn_output_171_cast_fp16)[name = tensor<string, []>("transpose_12")];
            tensor<fp16, [1, 77, 1280]> input_457_cast_fp16 = reshape(shape = var_2632, x = attn_output_173_cast_fp16)[name = tensor<string, []>("input_457_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_28_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(465080768))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(466309632))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(466309824)))];
            tensor<fp16, [1, 77, 1280]> linear_171_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_28_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_self_attn_out_proj_weight_to_fp16_palettized, x = input_457_cast_fp16)[name = tensor<string, []>("linear_171_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_459_cast_fp16 = add(x = input_451_cast_fp16, y = linear_171_cast_fp16)[name = tensor<string, []>("input_459_cast_fp16")];
            tensor<int32, [1]> input_461_axes_0 = const()[name = tensor<string, []>("input_461_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(466312448)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(466315072)))];
            tensor<fp16, [1, 77, 1280]> input_461_cast_fp16 = layer_norm(axes = input_461_axes_0, beta = text_encoder_text_model_encoder_layers_28_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_28_layer_norm2_weight_to_fp16, x = input_459_cast_fp16)[name = tensor<string, []>("input_461_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_28_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(466317696))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(471232960))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_28_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(471233152)))];
            tensor<fp16, [1, 77, 5120]> linear_172_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_28_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_mlp_fc1_weight_to_fp16_palettized, x = input_461_cast_fp16)[name = tensor<string, []>("linear_172_cast_fp16")];
            tensor<string, []> input_465_mode_0 = const()[name = tensor<string, []>("input_465_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_465_cast_fp16 = gelu(mode = input_465_mode_0, x = linear_172_cast_fp16)[name = tensor<string, []>("input_465_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_28_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(471243456))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(476158720))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(476158912)))];
            tensor<fp16, [1, 77, 1280]> linear_173_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_28_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_mlp_fc2_weight_to_fp16_palettized, x = input_465_cast_fp16)[name = tensor<string, []>("linear_173_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_467_cast_fp16 = add(x = input_459_cast_fp16, y = linear_173_cast_fp16)[name = tensor<string, []>("input_467_cast_fp16")];
            tensor<int32, [1]> hidden_states_175_axes_0 = const()[name = tensor<string, []>("hidden_states_175_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(476161536)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(476164160)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_175_cast_fp16 = layer_norm(axes = hidden_states_175_axes_0, beta = text_encoder_text_model_encoder_layers_29_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_29_layer_norm1_weight_to_fp16, x = input_467_cast_fp16)[name = tensor<string, []>("hidden_states_175_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_29_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(476166784))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(477395648))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(477395840)))];
            tensor<fp16, [1, 77, 1280]> linear_174_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_29_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_175_cast_fp16)[name = tensor<string, []>("linear_174_cast_fp16")];
            tensor<fp16, []> var_2671_to_fp16 = const()[name = tensor<string, []>("op_2671_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_179_cast_fp16 = mul(x = linear_174_cast_fp16, y = var_2671_to_fp16)[name = tensor<string, []>("tensor_179_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_29_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(477398464))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(478627328))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(478627520)))];
            tensor<fp16, [1, 77, 1280]> linear_175_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_29_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_175_cast_fp16)[name = tensor<string, []>("linear_175_cast_fp16")];
            tensor<int32, [4]> var_2676 = const()[name = tensor<string, []>("op_2676"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2677_cast_fp16 = reshape(shape = var_2676, x = linear_175_cast_fp16)[name = tensor<string, []>("op_2677_cast_fp16")];
            tensor<int32, [4]> var_2678_perm_0 = const()[name = tensor<string, []>("op_2678_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_29_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(478630144))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(479859008))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(479859200)))];
            tensor<fp16, [1, 77, 1280]> linear_176_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_29_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_175_cast_fp16)[name = tensor<string, []>("linear_176_cast_fp16")];
            tensor<int32, [4]> var_2683 = const()[name = tensor<string, []>("op_2683"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2684_cast_fp16 = reshape(shape = var_2683, x = linear_176_cast_fp16)[name = tensor<string, []>("op_2684_cast_fp16")];
            tensor<int32, [4]> var_2685_perm_0 = const()[name = tensor<string, []>("op_2685_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2692 = const()[name = tensor<string, []>("op_2692"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2693_cast_fp16 = reshape(shape = var_2692, x = tensor_179_cast_fp16)[name = tensor<string, []>("op_2693_cast_fp16")];
            tensor<int32, [4]> var_2694_perm_0 = const()[name = tensor<string, []>("op_2694_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2696 = const()[name = tensor<string, []>("op_2696"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2694_cast_fp16 = transpose(perm = var_2694_perm_0, x = var_2693_cast_fp16)[name = tensor<string, []>("transpose_11")];
            tensor<fp16, [20, 77, 64]> query_states_59_cast_fp16 = reshape(shape = var_2696, x = var_2694_cast_fp16)[name = tensor<string, []>("query_states_59_cast_fp16")];
            tensor<int32, [3]> var_2698 = const()[name = tensor<string, []>("op_2698"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2678_cast_fp16 = transpose(perm = var_2678_perm_0, x = var_2677_cast_fp16)[name = tensor<string, []>("transpose_10")];
            tensor<fp16, [20, 77, 64]> key_states_119_cast_fp16 = reshape(shape = var_2698, x = var_2678_cast_fp16)[name = tensor<string, []>("key_states_119_cast_fp16")];
            tensor<int32, [3]> var_2700 = const()[name = tensor<string, []>("op_2700"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2685_cast_fp16 = transpose(perm = var_2685_perm_0, x = var_2684_cast_fp16)[name = tensor<string, []>("transpose_9")];
            tensor<fp16, [20, 77, 64]> value_states_119_cast_fp16 = reshape(shape = var_2700, x = var_2685_cast_fp16)[name = tensor<string, []>("value_states_119_cast_fp16")];
            tensor<bool, []> attn_weights_175_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_175_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_175_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_175_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_175_cast_fp16 = matmul(transpose_x = attn_weights_175_transpose_x_1, transpose_y = attn_weights_175_transpose_y_1, x = query_states_59_cast_fp16, y = key_states_119_cast_fp16)[name = tensor<string, []>("attn_weights_175_cast_fp16")];
            tensor<int32, [4]> var_2705 = const()[name = tensor<string, []>("op_2705"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2706_cast_fp16 = reshape(shape = var_2705, x = attn_weights_175_cast_fp16)[name = tensor<string, []>("op_2706_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_177_cast_fp16 = add(x = var_2706_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_177_cast_fp16")];
            tensor<int32, [3]> var_2711 = const()[name = tensor<string, []>("op_2711"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_469_cast_fp16 = reshape(shape = var_2711, x = attn_weights_177_cast_fp16)[name = tensor<string, []>("input_469_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_471_cast_fp16 = softmax(axis = var_5, x = input_469_cast_fp16)[name = tensor<string, []>("input_471_cast_fp16")];
            tensor<bool, []> attn_output_175_transpose_x_0 = const()[name = tensor<string, []>("attn_output_175_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_175_transpose_y_0 = const()[name = tensor<string, []>("attn_output_175_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_175_cast_fp16 = matmul(transpose_x = attn_output_175_transpose_x_0, transpose_y = attn_output_175_transpose_y_0, x = input_471_cast_fp16, y = value_states_119_cast_fp16)[name = tensor<string, []>("attn_output_175_cast_fp16")];
            tensor<int32, [4]> var_2716 = const()[name = tensor<string, []>("op_2716"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_177_cast_fp16 = reshape(shape = var_2716, x = attn_output_175_cast_fp16)[name = tensor<string, []>("attn_output_177_cast_fp16")];
            tensor<int32, [4]> attn_output_179_perm_0 = const()[name = tensor<string, []>("attn_output_179_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2719 = const()[name = tensor<string, []>("op_2719"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_179_cast_fp16 = transpose(perm = attn_output_179_perm_0, x = attn_output_177_cast_fp16)[name = tensor<string, []>("transpose_8")];
            tensor<fp16, [1, 77, 1280]> input_473_cast_fp16 = reshape(shape = var_2719, x = attn_output_179_cast_fp16)[name = tensor<string, []>("input_473_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_29_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(479861824))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(481090688))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(481090880)))];
            tensor<fp16, [1, 77, 1280]> linear_177_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_29_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_self_attn_out_proj_weight_to_fp16_palettized, x = input_473_cast_fp16)[name = tensor<string, []>("linear_177_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_475_cast_fp16 = add(x = input_467_cast_fp16, y = linear_177_cast_fp16)[name = tensor<string, []>("input_475_cast_fp16")];
            tensor<int32, [1]> input_477_axes_0 = const()[name = tensor<string, []>("input_477_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(481093504)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(481096128)))];
            tensor<fp16, [1, 77, 1280]> input_477_cast_fp16 = layer_norm(axes = input_477_axes_0, beta = text_encoder_text_model_encoder_layers_29_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_29_layer_norm2_weight_to_fp16, x = input_475_cast_fp16)[name = tensor<string, []>("input_477_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_29_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(481098752))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(486014016))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_29_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(486014208)))];
            tensor<fp16, [1, 77, 5120]> linear_178_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_29_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_mlp_fc1_weight_to_fp16_palettized, x = input_477_cast_fp16)[name = tensor<string, []>("linear_178_cast_fp16")];
            tensor<string, []> input_481_mode_0 = const()[name = tensor<string, []>("input_481_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_481_cast_fp16 = gelu(mode = input_481_mode_0, x = linear_178_cast_fp16)[name = tensor<string, []>("input_481_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_29_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(486024512))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(490939776))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(490939968)))];
            tensor<fp16, [1, 77, 1280]> linear_179_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_29_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_mlp_fc2_weight_to_fp16_palettized, x = input_481_cast_fp16)[name = tensor<string, []>("linear_179_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_483_cast_fp16 = add(x = input_475_cast_fp16, y = linear_179_cast_fp16)[name = tensor<string, []>("input_483_cast_fp16")];
            tensor<int32, [1]> hidden_states_181_axes_0 = const()[name = tensor<string, []>("hidden_states_181_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(490942592)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(490945216)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_181_cast_fp16 = layer_norm(axes = hidden_states_181_axes_0, beta = text_encoder_text_model_encoder_layers_30_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_30_layer_norm1_weight_to_fp16, x = input_483_cast_fp16)[name = tensor<string, []>("hidden_states_181_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_30_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(490947840))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(492176704))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(492176896)))];
            tensor<fp16, [1, 77, 1280]> linear_180_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_30_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_181_cast_fp16)[name = tensor<string, []>("linear_180_cast_fp16")];
            tensor<fp16, []> var_2758_to_fp16 = const()[name = tensor<string, []>("op_2758_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_185_cast_fp16 = mul(x = linear_180_cast_fp16, y = var_2758_to_fp16)[name = tensor<string, []>("tensor_185_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_30_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(492179520))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(493408384))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(493408576)))];
            tensor<fp16, [1, 77, 1280]> linear_181_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_30_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_181_cast_fp16)[name = tensor<string, []>("linear_181_cast_fp16")];
            tensor<int32, [4]> var_2763 = const()[name = tensor<string, []>("op_2763"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2764_cast_fp16 = reshape(shape = var_2763, x = linear_181_cast_fp16)[name = tensor<string, []>("op_2764_cast_fp16")];
            tensor<int32, [4]> var_2765_perm_0 = const()[name = tensor<string, []>("op_2765_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_30_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(493411200))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(494640064))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(494640256)))];
            tensor<fp16, [1, 77, 1280]> linear_182_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_30_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_181_cast_fp16)[name = tensor<string, []>("linear_182_cast_fp16")];
            tensor<int32, [4]> var_2770 = const()[name = tensor<string, []>("op_2770"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2771_cast_fp16 = reshape(shape = var_2770, x = linear_182_cast_fp16)[name = tensor<string, []>("op_2771_cast_fp16")];
            tensor<int32, [4]> var_2772_perm_0 = const()[name = tensor<string, []>("op_2772_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2779 = const()[name = tensor<string, []>("op_2779"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2780_cast_fp16 = reshape(shape = var_2779, x = tensor_185_cast_fp16)[name = tensor<string, []>("op_2780_cast_fp16")];
            tensor<int32, [4]> var_2781_perm_0 = const()[name = tensor<string, []>("op_2781_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2783 = const()[name = tensor<string, []>("op_2783"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2781_cast_fp16 = transpose(perm = var_2781_perm_0, x = var_2780_cast_fp16)[name = tensor<string, []>("transpose_7")];
            tensor<fp16, [20, 77, 64]> query_states_61_cast_fp16 = reshape(shape = var_2783, x = var_2781_cast_fp16)[name = tensor<string, []>("query_states_61_cast_fp16")];
            tensor<int32, [3]> var_2785 = const()[name = tensor<string, []>("op_2785"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2765_cast_fp16 = transpose(perm = var_2765_perm_0, x = var_2764_cast_fp16)[name = tensor<string, []>("transpose_6")];
            tensor<fp16, [20, 77, 64]> key_states_123_cast_fp16 = reshape(shape = var_2785, x = var_2765_cast_fp16)[name = tensor<string, []>("key_states_123_cast_fp16")];
            tensor<int32, [3]> var_2787 = const()[name = tensor<string, []>("op_2787"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2772_cast_fp16 = transpose(perm = var_2772_perm_0, x = var_2771_cast_fp16)[name = tensor<string, []>("transpose_5")];
            tensor<fp16, [20, 77, 64]> value_states_123_cast_fp16 = reshape(shape = var_2787, x = var_2772_cast_fp16)[name = tensor<string, []>("value_states_123_cast_fp16")];
            tensor<bool, []> attn_weights_181_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_181_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_181_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_181_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_181_cast_fp16 = matmul(transpose_x = attn_weights_181_transpose_x_1, transpose_y = attn_weights_181_transpose_y_1, x = query_states_61_cast_fp16, y = key_states_123_cast_fp16)[name = tensor<string, []>("attn_weights_181_cast_fp16")];
            tensor<int32, [4]> var_2792 = const()[name = tensor<string, []>("op_2792"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2793_cast_fp16 = reshape(shape = var_2792, x = attn_weights_181_cast_fp16)[name = tensor<string, []>("op_2793_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_183_cast_fp16 = add(x = var_2793_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_183_cast_fp16")];
            tensor<int32, [3]> var_2798 = const()[name = tensor<string, []>("op_2798"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_485_cast_fp16 = reshape(shape = var_2798, x = attn_weights_183_cast_fp16)[name = tensor<string, []>("input_485_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_487_cast_fp16 = softmax(axis = var_5, x = input_485_cast_fp16)[name = tensor<string, []>("input_487_cast_fp16")];
            tensor<bool, []> attn_output_181_transpose_x_0 = const()[name = tensor<string, []>("attn_output_181_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_181_transpose_y_0 = const()[name = tensor<string, []>("attn_output_181_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_181_cast_fp16 = matmul(transpose_x = attn_output_181_transpose_x_0, transpose_y = attn_output_181_transpose_y_0, x = input_487_cast_fp16, y = value_states_123_cast_fp16)[name = tensor<string, []>("attn_output_181_cast_fp16")];
            tensor<int32, [4]> var_2803 = const()[name = tensor<string, []>("op_2803"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_183_cast_fp16 = reshape(shape = var_2803, x = attn_output_181_cast_fp16)[name = tensor<string, []>("attn_output_183_cast_fp16")];
            tensor<int32, [4]> attn_output_185_perm_0 = const()[name = tensor<string, []>("attn_output_185_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2806 = const()[name = tensor<string, []>("op_2806"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_185_cast_fp16 = transpose(perm = attn_output_185_perm_0, x = attn_output_183_cast_fp16)[name = tensor<string, []>("transpose_4")];
            tensor<fp16, [1, 77, 1280]> input_489_cast_fp16 = reshape(shape = var_2806, x = attn_output_185_cast_fp16)[name = tensor<string, []>("input_489_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_30_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(494642880))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(495871744))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(495871936)))];
            tensor<fp16, [1, 77, 1280]> linear_183_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_30_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_self_attn_out_proj_weight_to_fp16_palettized, x = input_489_cast_fp16)[name = tensor<string, []>("linear_183_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_491_cast_fp16 = add(x = input_483_cast_fp16, y = linear_183_cast_fp16)[name = tensor<string, []>("input_491_cast_fp16")];
            tensor<int32, [1]> input_493_axes_0 = const()[name = tensor<string, []>("input_493_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(495874560)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(495877184)))];
            tensor<fp16, [1, 77, 1280]> input_493_cast_fp16 = layer_norm(axes = input_493_axes_0, beta = text_encoder_text_model_encoder_layers_30_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_30_layer_norm2_weight_to_fp16, x = input_491_cast_fp16)[name = tensor<string, []>("input_493_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_30_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(495879808))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(500795072))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_30_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(500795264)))];
            tensor<fp16, [1, 77, 5120]> linear_184_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_30_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_mlp_fc1_weight_to_fp16_palettized, x = input_493_cast_fp16)[name = tensor<string, []>("linear_184_cast_fp16")];
            tensor<string, []> input_497_mode_0 = const()[name = tensor<string, []>("input_497_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_497_cast_fp16 = gelu(mode = input_497_mode_0, x = linear_184_cast_fp16)[name = tensor<string, []>("input_497_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_30_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(500805568))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(505720832))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(505721024)))];
            tensor<fp16, [1, 77, 1280]> linear_185_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_30_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_mlp_fc2_weight_to_fp16_palettized, x = input_497_cast_fp16)[name = tensor<string, []>("linear_185_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_499_cast_fp16 = add(x = input_491_cast_fp16, y = linear_185_cast_fp16)[name = tensor<string, []>("input_499_cast_fp16")];
            tensor<string, []> input_499_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("input_499_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<int32, [1]> hidden_states_187_axes_0 = const()[name = tensor<string, []>("hidden_states_187_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(505723648)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(505726272)))];
            tensor<fp16, [1, 77, 1280]> hidden_states_187_cast_fp16 = layer_norm(axes = hidden_states_187_axes_0, beta = text_encoder_text_model_encoder_layers_31_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_31_layer_norm1_weight_to_fp16, x = input_499_cast_fp16)[name = tensor<string, []>("hidden_states_187_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_31_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(505728896))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(506957760))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(506957952)))];
            tensor<fp16, [1, 77, 1280]> linear_186_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_31_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_187_cast_fp16)[name = tensor<string, []>("linear_186_cast_fp16")];
            tensor<fp16, []> var_2845_to_fp16 = const()[name = tensor<string, []>("op_2845_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
            tensor<fp16, [1, 77, 1280]> tensor_cast_fp16 = mul(x = linear_186_cast_fp16, y = var_2845_to_fp16)[name = tensor<string, []>("tensor_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_31_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(506960576))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(508189440))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(508189632)))];
            tensor<fp16, [1, 77, 1280]> linear_187_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_31_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_187_cast_fp16)[name = tensor<string, []>("linear_187_cast_fp16")];
            tensor<int32, [4]> var_2850 = const()[name = tensor<string, []>("op_2850"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2851_cast_fp16 = reshape(shape = var_2850, x = linear_187_cast_fp16)[name = tensor<string, []>("op_2851_cast_fp16")];
            tensor<int32, [4]> var_2852_perm_0 = const()[name = tensor<string, []>("op_2852_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_31_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(508192256))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(509421120))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(509421312)))];
            tensor<fp16, [1, 77, 1280]> linear_188_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_31_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_187_cast_fp16)[name = tensor<string, []>("linear_188_cast_fp16")];
            tensor<int32, [4]> var_2857 = const()[name = tensor<string, []>("op_2857"), val = tensor<int32, [4]>([1, -1, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2858_cast_fp16 = reshape(shape = var_2857, x = linear_188_cast_fp16)[name = tensor<string, []>("op_2858_cast_fp16")];
            tensor<int32, [4]> var_2859_perm_0 = const()[name = tensor<string, []>("op_2859_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [4]> var_2866 = const()[name = tensor<string, []>("op_2866"), val = tensor<int32, [4]>([1, 77, 20, 64])];
            tensor<fp16, [1, 77, 20, 64]> var_2867_cast_fp16 = reshape(shape = var_2866, x = tensor_cast_fp16)[name = tensor<string, []>("op_2867_cast_fp16")];
            tensor<int32, [4]> var_2868_perm_0 = const()[name = tensor<string, []>("op_2868_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2870 = const()[name = tensor<string, []>("op_2870"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2868_cast_fp16 = transpose(perm = var_2868_perm_0, x = var_2867_cast_fp16)[name = tensor<string, []>("transpose_3")];
            tensor<fp16, [20, 77, 64]> query_states_cast_fp16 = reshape(shape = var_2870, x = var_2868_cast_fp16)[name = tensor<string, []>("query_states_cast_fp16")];
            tensor<int32, [3]> var_2872 = const()[name = tensor<string, []>("op_2872"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2852_cast_fp16 = transpose(perm = var_2852_perm_0, x = var_2851_cast_fp16)[name = tensor<string, []>("transpose_2")];
            tensor<fp16, [20, 77, 64]> key_states_cast_fp16 = reshape(shape = var_2872, x = var_2852_cast_fp16)[name = tensor<string, []>("key_states_cast_fp16")];
            tensor<int32, [3]> var_2874 = const()[name = tensor<string, []>("op_2874"), val = tensor<int32, [3]>([20, -1, 64])];
            tensor<fp16, [1, 20, 77, 64]> var_2859_cast_fp16 = transpose(perm = var_2859_perm_0, x = var_2858_cast_fp16)[name = tensor<string, []>("transpose_1")];
            tensor<fp16, [20, 77, 64]> value_states_cast_fp16 = reshape(shape = var_2874, x = var_2859_cast_fp16)[name = tensor<string, []>("value_states_cast_fp16")];
            tensor<bool, []> attn_weights_187_transpose_x_1 = const()[name = tensor<string, []>("attn_weights_187_transpose_x_1"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_weights_187_transpose_y_1 = const()[name = tensor<string, []>("attn_weights_187_transpose_y_1"), val = tensor<bool, []>(true)];
            tensor<fp16, [20, 77, 77]> attn_weights_187_cast_fp16 = matmul(transpose_x = attn_weights_187_transpose_x_1, transpose_y = attn_weights_187_transpose_y_1, x = query_states_cast_fp16, y = key_states_cast_fp16)[name = tensor<string, []>("attn_weights_187_cast_fp16")];
            tensor<int32, [4]> var_2879 = const()[name = tensor<string, []>("op_2879"), val = tensor<int32, [4]>([1, 20, 77, 77])];
            tensor<fp16, [1, 20, 77, 77]> var_2880_cast_fp16 = reshape(shape = var_2879, x = attn_weights_187_cast_fp16)[name = tensor<string, []>("op_2880_cast_fp16")];
            tensor<fp16, [1, 20, 77, 77]> attn_weights_189_cast_fp16 = add(x = var_2880_cast_fp16, y = op_58_to_fp16_palettized)[name = tensor<string, []>("attn_weights_189_cast_fp16")];
            tensor<int32, [3]> var_2885 = const()[name = tensor<string, []>("op_2885"), val = tensor<int32, [3]>([20, 77, 77])];
            tensor<fp16, [20, 77, 77]> input_501_cast_fp16 = reshape(shape = var_2885, x = attn_weights_189_cast_fp16)[name = tensor<string, []>("input_501_cast_fp16")];
            tensor<fp16, [20, 77, 77]> input_503_cast_fp16 = softmax(axis = var_5, x = input_501_cast_fp16)[name = tensor<string, []>("input_503_cast_fp16")];
            tensor<bool, []> attn_output_187_transpose_x_0 = const()[name = tensor<string, []>("attn_output_187_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> attn_output_187_transpose_y_0 = const()[name = tensor<string, []>("attn_output_187_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [20, 77, 64]> attn_output_187_cast_fp16 = matmul(transpose_x = attn_output_187_transpose_x_0, transpose_y = attn_output_187_transpose_y_0, x = input_503_cast_fp16, y = value_states_cast_fp16)[name = tensor<string, []>("attn_output_187_cast_fp16")];
            tensor<int32, [4]> var_2890 = const()[name = tensor<string, []>("op_2890"), val = tensor<int32, [4]>([1, 20, 77, 64])];
            tensor<fp16, [1, 20, 77, 64]> attn_output_189_cast_fp16 = reshape(shape = var_2890, x = attn_output_187_cast_fp16)[name = tensor<string, []>("attn_output_189_cast_fp16")];
            tensor<int32, [4]> attn_output_perm_0 = const()[name = tensor<string, []>("attn_output_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2893 = const()[name = tensor<string, []>("op_2893"), val = tensor<int32, [3]>([1, 77, 1280])];
            tensor<fp16, [1, 77, 20, 64]> attn_output_cast_fp16 = transpose(perm = attn_output_perm_0, x = attn_output_189_cast_fp16)[name = tensor<string, []>("transpose_0")];
            tensor<fp16, [1, 77, 1280]> input_505_cast_fp16 = reshape(shape = var_2893, x = attn_output_cast_fp16)[name = tensor<string, []>("input_505_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_31_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(509423936))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(510652800))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(510652992)))];
            tensor<fp16, [1, 77, 1280]> linear_189_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_31_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_self_attn_out_proj_weight_to_fp16_palettized, x = input_505_cast_fp16)[name = tensor<string, []>("linear_189_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_507_cast_fp16 = add(x = input_499_cast_fp16, y = linear_189_cast_fp16)[name = tensor<string, []>("input_507_cast_fp16")];
            tensor<int32, [1]> input_509_axes_0 = const()[name = tensor<string, []>("input_509_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(510655616)))];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(510658240)))];
            tensor<fp16, [1, 77, 1280]> input_509_cast_fp16 = layer_norm(axes = input_509_axes_0, beta = text_encoder_text_model_encoder_layers_31_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_31_layer_norm2_weight_to_fp16, x = input_507_cast_fp16)[name = tensor<string, []>("input_509_cast_fp16")];
            tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_31_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(510660864))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(515576128))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_mlp_fc1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([5120, 1280])];
            tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_31_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(515576320)))];
            tensor<fp16, [1, 77, 5120]> linear_190_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_31_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_mlp_fc1_weight_to_fp16_palettized, x = input_509_cast_fp16)[name = tensor<string, []>("linear_190_cast_fp16")];
            tensor<string, []> input_513_mode_0 = const()[name = tensor<string, []>("input_513_mode_0"), val = tensor<string, []>("EXACT")];
            tensor<fp16, [1, 77, 5120]> input_513_cast_fp16 = gelu(mode = input_513_mode_0, x = linear_190_cast_fp16)[name = tensor<string, []>("input_513_cast_fp16")];
            tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_31_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [4915200]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(515586624))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(520501888))), name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_mlp_fc2_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 5120])];
            tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(520502080)))];
            tensor<fp16, [1, 77, 1280]> linear_191_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_31_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_mlp_fc2_weight_to_fp16_palettized, x = input_513_cast_fp16)[name = tensor<string, []>("linear_191_cast_fp16")];
            tensor<fp16, [1, 77, 1280]> input_515_cast_fp16 = add(x = input_507_cast_fp16, y = linear_191_cast_fp16)[name = tensor<string, []>("input_515_cast_fp16")];
            tensor<int32, [1]> last_hidden_state_axes_0 = const()[name = tensor<string, []>("last_hidden_state_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1280]> text_encoder_text_model_final_layer_norm_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_final_layer_norm_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(520504704)))];
            tensor<fp16, [1280]> text_encoder_text_model_final_layer_norm_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_final_layer_norm_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(520507328)))];
            tensor<fp16, [1, 77, 1280]> last_hidden_state_cast_fp16 = layer_norm(axes = last_hidden_state_axes_0, beta = text_encoder_text_model_final_layer_norm_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_final_layer_norm_weight_to_fp16, x = input_515_cast_fp16)[name = tensor<string, []>("last_hidden_state_cast_fp16")];
            tensor<int32, [1]> var_2921 = const()[name = tensor<string, []>("op_2921"), val = tensor<int32, [1]>([0])];
            tensor<int32, []> var_2923_axis_0 = const()[name = tensor<string, []>("op_2923_axis_0"), val = tensor<int32, []>(-1)];
            tensor<bool, []> var_2923_keep_dims_0 = const()[name = tensor<string, []>("op_2923_keep_dims_0"), val = tensor<bool, []>(false)];
            tensor<int32, [1]> var_2923 = reduce_argmax(axis = var_2923_axis_0, keep_dims = var_2923_keep_dims_0, x = cast_1)[name = tensor<string, []>("op_2923")];
            tensor<int32, []> stack_0_axis_0 = const()[name = tensor<string, []>("stack_0_axis_0"), val = tensor<int32, []>(1)];
            tensor<int32, [1, 2]> stack_0 = stack(axis = stack_0_axis_0, values = (var_2921, var_2923))[name = tensor<string, []>("stack_0")];
            tensor<int32, []> input_transpose_batch_dims_0 = const()[name = tensor<string, []>("input_transpose_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<fp16, [1, 1280]> input_transpose_cast_fp16 = gather_nd(batch_dims = input_transpose_batch_dims_0, indices = stack_0, x = last_hidden_state_cast_fp16)[name = tensor<string, []>("input_transpose_cast_fp16")];
            tensor<fp16, [1280, 1280]> text_encoder_text_projection_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [1228800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(520509952))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(521738816))), name = tensor<string, []>("text_encoder_text_projection_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([1280, 1280])];
            tensor<fp16, [1280]> linear_192_bias_0_to_fp16 = const()[name = tensor<string, []>("linear_192_bias_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(521739008)))];
            tensor<fp16, [1, 1280]> linear_192_cast_fp16 = linear(bias = linear_192_bias_0_to_fp16, weight = text_encoder_text_projection_weight_to_fp16_palettized, x = input_transpose_cast_fp16)[name = tensor<string, []>("linear_192_cast_fp16")];
            tensor<string, []> linear_192_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("linear_192_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<fp32, [1, 77, 1280]> hidden_embeds = cast(dtype = input_499_cast_fp16_to_fp32_dtype_0, x = input_499_cast_fp16)[name = tensor<string, []>("cast_0")];
            tensor<fp32, [1, 1280]> pooled_outputs = cast(dtype = linear_192_cast_fp16_to_fp32_dtype_0, x = linear_192_cast_fp16)[name = tensor<string, []>("cast_1")];
        } -> (hidden_embeds, pooled_outputs);
}