| program(1.0) |
| [buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "5.33.5"}, {"coremlc-version", "1877.40.3"}, {"coremltools-component-torch", "2.0.1"}, {"coremltools-version", "7.0b2"}})] |
| { |
| func main<ios16>(tensor<fp32, [1, 77]> input_ids) { |
| tensor<int32, []> var_5 = const()[name = tensor<string, []>("op_5"), val = tensor<int32, []>(-1)]; |
| tensor<bool, []> var_6 = const()[name = tensor<string, []>("op_6"), val = tensor<bool, []>(false)]; |
| 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 = const()[name = tensor<string, []>("text_encoder_text_model_embeddings_token_embedding_weight_to_fp16"), val = tensor<fp16, [49408, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))]; |
| tensor<int32, [1, 77]> cast_1326 = cast(dtype = cast_1_dtype_0, x = input_ids)[name = tensor<string, []>("cast_1326")]; |
| tensor<fp16, [1, 77, 1280]> inputs_embeds_cast = gather(axis = inputs_embeds_axis_0, batch_dims = inputs_embeds_batch_dims_0, indices = cast_1326, x = text_encoder_text_model_embeddings_token_embedding_weight_to_fp16)[name = tensor<string, []>("inputs_embeds_cast")]; |
| tensor<fp16, [1, 77, 1280]> position_embeddings_to_fp16 = const()[name = tensor<string, []>("position_embeddings_to_fp16"), val = tensor<fp16, [1, 77, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126484608)))]; |
| tensor<fp16, [1, 77, 1280]> input_3_cast = add(x = inputs_embeds_cast, y = position_embeddings_to_fp16)[name = tensor<string, []>("input_3_cast")]; |
| 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, []>(126681792)))]; |
| 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, []>(126684416)))]; |
| 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 = 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)[name = tensor<string, []>("hidden_states_1_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126687040)))]; |
| 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, []>(129963904)))]; |
| tensor<fp16, [1, 77, 1280]> var_148_cast = 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, x = hidden_states_1_cast)[name = tensor<string, []>("op_148_cast")]; |
| tensor<fp16, []> var_149_to_fp16 = const()[name = tensor<string, []>("op_149_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_5_cast = mul(x = var_148_cast, y = var_149_to_fp16)[name = tensor<string, []>("tensor_5_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(129966528)))]; |
| 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, []>(133243392)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_1_cast = 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, x = hidden_states_1_cast)[name = tensor<string, []>("tensor_1_cast")]; |
| tensor<int32, [4]> var_154 = const()[name = tensor<string, []>("op_154"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_155_cast = reshape(shape = var_154, x = tensor_1_cast)[name = tensor<string, []>("op_155_cast")]; |
| tensor<int32, [4]> var_156_perm_0 = const()[name = tensor<string, []>("op_156_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133246016)))]; |
| 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, []>(136522880)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_3_cast = 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, x = hidden_states_1_cast)[name = tensor<string, []>("tensor_3_cast")]; |
| tensor<int32, [4]> var_161 = const()[name = tensor<string, []>("op_161"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_162_cast = reshape(shape = var_161, x = tensor_3_cast)[name = tensor<string, []>("op_162_cast")]; |
| tensor<int32, [4]> var_163_perm_0 = const()[name = tensor<string, []>("op_163_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_170 = const()[name = tensor<string, []>("op_170"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_171_cast = reshape(shape = var_170, x = tensor_5_cast)[name = tensor<string, []>("op_171_cast")]; |
| tensor<int32, [4]> var_172_perm_0 = const()[name = tensor<string, []>("op_172_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_174 = const()[name = tensor<string, []>("op_174"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_158 = transpose(perm = var_172_perm_0, x = var_171_cast)[name = tensor<string, []>("transpose_158")]; |
| tensor<fp16, [20, 77, 64]> query_states_1_cast = reshape(shape = var_174, x = transpose_158)[name = tensor<string, []>("query_states_1_cast")]; |
| tensor<int32, [3]> var_176 = const()[name = tensor<string, []>("op_176"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_160 = transpose(perm = var_156_perm_0, x = var_155_cast)[name = tensor<string, []>("transpose_160")]; |
| tensor<fp16, [20, 77, 64]> key_states_3_cast = reshape(shape = var_176, x = transpose_160)[name = tensor<string, []>("key_states_3_cast")]; |
| tensor<int32, [3]> var_178 = const()[name = tensor<string, []>("op_178"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_159 = transpose(perm = var_163_perm_0, x = var_162_cast)[name = tensor<string, []>("transpose_159")]; |
| tensor<fp16, [20, 77, 64]> value_states_3_cast = reshape(shape = var_178, x = transpose_159)[name = tensor<string, []>("value_states_3_cast")]; |
| tensor<int32, [3]> var_181_perm_0 = const()[name = tensor<string, []>("op_181_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_1_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_1_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_1_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_1_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_157 = transpose(perm = var_181_perm_0, x = key_states_3_cast)[name = tensor<string, []>("transpose_157")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_1_cast = matmul(transpose_x = attn_weights_1_transpose_x_0, transpose_y = attn_weights_1_transpose_y_0, x = query_states_1_cast, y = transpose_157)[name = tensor<string, []>("attn_weights_1_cast")]; |
| tensor<int32, [4]> var_183 = const()[name = tensor<string, []>("op_183"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_184_cast = reshape(shape = var_183, x = attn_weights_1_cast)[name = tensor<string, []>("op_184_cast")]; |
| tensor<fp16, [1, 1, 77, 77]> var_58_to_fp16 = const()[name = tensor<string, []>("op_58_to_fp16"), val = tensor<fp16, [1, 1, 77, 77]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136525504)))]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_3_cast = add(x = var_184_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_3_cast")]; |
| tensor<int32, [3]> var_189 = const()[name = tensor<string, []>("op_189"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_5_cast = reshape(shape = var_189, x = attn_weights_3_cast)[name = tensor<string, []>("input_5_cast")]; |
| tensor<fp16, [20, 77, 77]> input_7_cast = softmax(axis = var_5, x = input_5_cast)[name = tensor<string, []>("input_7_cast")]; |
| 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 = matmul(transpose_x = attn_output_1_transpose_x_0, transpose_y = attn_output_1_transpose_y_0, x = input_7_cast, y = value_states_3_cast)[name = tensor<string, []>("attn_output_1_cast")]; |
| tensor<int32, [4]> var_194 = const()[name = tensor<string, []>("op_194"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_3_cast = reshape(shape = var_194, x = attn_output_1_cast)[name = tensor<string, []>("attn_output_3_cast")]; |
| 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_197 = const()[name = tensor<string, []>("op_197"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_156 = transpose(perm = attn_output_5_perm_0, x = attn_output_3_cast)[name = tensor<string, []>("transpose_156")]; |
| tensor<fp16, [1, 77, 1280]> input_9_cast = reshape(shape = var_197, x = transpose_156)[name = tensor<string, []>("input_9_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136537472)))]; |
| 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, []>(139814336)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_3_cast = 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, x = input_9_cast)[name = tensor<string, []>("hidden_states_3_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_11_cast = add(x = input_3_cast, y = hidden_states_3_cast)[name = tensor<string, []>("input_11_cast")]; |
| 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, []>(139816960)))]; |
| 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, []>(139819584)))]; |
| tensor<fp16, [1, 77, 1280]> input_13_cast = 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)[name = tensor<string, []>("input_13_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139822208)))]; |
| 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, []>(152929472)))]; |
| tensor<fp16, [1, 77, 5120]> input_15_cast = 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, x = input_13_cast)[name = tensor<string, []>("input_15_cast")]; |
| 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 = gelu(mode = input_17_mode_0, x = input_15_cast)[name = tensor<string, []>("input_17_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152939776)))]; |
| 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, []>(166047040)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_5_cast = 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, x = input_17_cast)[name = tensor<string, []>("hidden_states_5_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_19_cast = add(x = input_11_cast, y = hidden_states_5_cast)[name = tensor<string, []>("input_19_cast")]; |
| 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, []>(166049664)))]; |
| 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, []>(166052288)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_7_cast = 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)[name = tensor<string, []>("hidden_states_7_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166054912)))]; |
| 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, []>(169331776)))]; |
| tensor<fp16, [1, 77, 1280]> var_235_cast = 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, x = hidden_states_7_cast)[name = tensor<string, []>("op_235_cast")]; |
| tensor<fp16, []> var_236_to_fp16 = const()[name = tensor<string, []>("op_236_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_11_cast = mul(x = var_235_cast, y = var_236_to_fp16)[name = tensor<string, []>("tensor_11_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(169334400)))]; |
| 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, []>(172611264)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_7_cast = 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, x = hidden_states_7_cast)[name = tensor<string, []>("tensor_7_cast")]; |
| tensor<int32, [4]> var_241 = const()[name = tensor<string, []>("op_241"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_242_cast = reshape(shape = var_241, x = tensor_7_cast)[name = tensor<string, []>("op_242_cast")]; |
| tensor<int32, [4]> var_243_perm_0 = const()[name = tensor<string, []>("op_243_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172613888)))]; |
| 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, []>(175890752)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_9_cast = 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, x = hidden_states_7_cast)[name = tensor<string, []>("tensor_9_cast")]; |
| tensor<int32, [4]> var_248 = const()[name = tensor<string, []>("op_248"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_249_cast = reshape(shape = var_248, x = tensor_9_cast)[name = tensor<string, []>("op_249_cast")]; |
| tensor<int32, [4]> var_250_perm_0 = const()[name = tensor<string, []>("op_250_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_257 = const()[name = tensor<string, []>("op_257"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_258_cast = reshape(shape = var_257, x = tensor_11_cast)[name = tensor<string, []>("op_258_cast")]; |
| tensor<int32, [4]> var_259_perm_0 = const()[name = tensor<string, []>("op_259_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_261 = const()[name = tensor<string, []>("op_261"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_153 = transpose(perm = var_259_perm_0, x = var_258_cast)[name = tensor<string, []>("transpose_153")]; |
| tensor<fp16, [20, 77, 64]> query_states_3_cast = reshape(shape = var_261, x = transpose_153)[name = tensor<string, []>("query_states_3_cast")]; |
| tensor<int32, [3]> var_263 = const()[name = tensor<string, []>("op_263"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_155 = transpose(perm = var_243_perm_0, x = var_242_cast)[name = tensor<string, []>("transpose_155")]; |
| tensor<fp16, [20, 77, 64]> key_states_7_cast = reshape(shape = var_263, x = transpose_155)[name = tensor<string, []>("key_states_7_cast")]; |
| tensor<int32, [3]> var_265 = const()[name = tensor<string, []>("op_265"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_154 = transpose(perm = var_250_perm_0, x = var_249_cast)[name = tensor<string, []>("transpose_154")]; |
| tensor<fp16, [20, 77, 64]> value_states_7_cast = reshape(shape = var_265, x = transpose_154)[name = tensor<string, []>("value_states_7_cast")]; |
| tensor<int32, [3]> var_268_perm_0 = const()[name = tensor<string, []>("op_268_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_7_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_7_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_7_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_7_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_152 = transpose(perm = var_268_perm_0, x = key_states_7_cast)[name = tensor<string, []>("transpose_152")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_7_cast = matmul(transpose_x = attn_weights_7_transpose_x_0, transpose_y = attn_weights_7_transpose_y_0, x = query_states_3_cast, y = transpose_152)[name = tensor<string, []>("attn_weights_7_cast")]; |
| tensor<int32, [4]> var_270 = const()[name = tensor<string, []>("op_270"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_271_cast = reshape(shape = var_270, x = attn_weights_7_cast)[name = tensor<string, []>("op_271_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_9_cast = add(x = var_271_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_9_cast")]; |
| tensor<int32, [3]> var_276 = const()[name = tensor<string, []>("op_276"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_21_cast = reshape(shape = var_276, x = attn_weights_9_cast)[name = tensor<string, []>("input_21_cast")]; |
| tensor<fp16, [20, 77, 77]> input_23_cast = softmax(axis = var_5, x = input_21_cast)[name = tensor<string, []>("input_23_cast")]; |
| 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 = matmul(transpose_x = attn_output_7_transpose_x_0, transpose_y = attn_output_7_transpose_y_0, x = input_23_cast, y = value_states_7_cast)[name = tensor<string, []>("attn_output_7_cast")]; |
| tensor<int32, [4]> var_281 = const()[name = tensor<string, []>("op_281"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_9_cast = reshape(shape = var_281, x = attn_output_7_cast)[name = tensor<string, []>("attn_output_9_cast")]; |
| 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_284 = const()[name = tensor<string, []>("op_284"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_151 = transpose(perm = attn_output_11_perm_0, x = attn_output_9_cast)[name = tensor<string, []>("transpose_151")]; |
| tensor<fp16, [1, 77, 1280]> input_25_cast = reshape(shape = var_284, x = transpose_151)[name = tensor<string, []>("input_25_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(175893376)))]; |
| 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, []>(179170240)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_9_cast = 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, x = input_25_cast)[name = tensor<string, []>("hidden_states_9_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_27_cast = add(x = input_19_cast, y = hidden_states_9_cast)[name = tensor<string, []>("input_27_cast")]; |
| 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, []>(179172864)))]; |
| 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, []>(179175488)))]; |
| tensor<fp16, [1, 77, 1280]> input_29_cast = 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)[name = tensor<string, []>("input_29_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(179178112)))]; |
| 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, []>(192285376)))]; |
| tensor<fp16, [1, 77, 5120]> input_31_cast = 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, x = input_29_cast)[name = tensor<string, []>("input_31_cast")]; |
| 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 = gelu(mode = input_33_mode_0, x = input_31_cast)[name = tensor<string, []>("input_33_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(192295680)))]; |
| 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, []>(205402944)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_11_cast = 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, x = input_33_cast)[name = tensor<string, []>("hidden_states_11_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_35_cast = add(x = input_27_cast, y = hidden_states_11_cast)[name = tensor<string, []>("input_35_cast")]; |
| 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, []>(205405568)))]; |
| 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, []>(205408192)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_13_cast = 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)[name = tensor<string, []>("hidden_states_13_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205410816)))]; |
| 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, []>(208687680)))]; |
| tensor<fp16, [1, 77, 1280]> var_322_cast = 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, x = hidden_states_13_cast)[name = tensor<string, []>("op_322_cast")]; |
| tensor<fp16, []> var_323_to_fp16 = const()[name = tensor<string, []>("op_323_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_17_cast = mul(x = var_322_cast, y = var_323_to_fp16)[name = tensor<string, []>("tensor_17_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(208690304)))]; |
| 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, []>(211967168)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_13_cast = 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, x = hidden_states_13_cast)[name = tensor<string, []>("tensor_13_cast")]; |
| tensor<int32, [4]> var_328 = const()[name = tensor<string, []>("op_328"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_329_cast = reshape(shape = var_328, x = tensor_13_cast)[name = tensor<string, []>("op_329_cast")]; |
| tensor<int32, [4]> var_330_perm_0 = const()[name = tensor<string, []>("op_330_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211969792)))]; |
| 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, []>(215246656)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_15_cast = 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, x = hidden_states_13_cast)[name = tensor<string, []>("tensor_15_cast")]; |
| tensor<int32, [4]> var_335 = const()[name = tensor<string, []>("op_335"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_336_cast = reshape(shape = var_335, x = tensor_15_cast)[name = tensor<string, []>("op_336_cast")]; |
| tensor<int32, [4]> var_337_perm_0 = const()[name = tensor<string, []>("op_337_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_344 = const()[name = tensor<string, []>("op_344"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_345_cast = reshape(shape = var_344, x = tensor_17_cast)[name = tensor<string, []>("op_345_cast")]; |
| tensor<int32, [4]> var_346_perm_0 = const()[name = tensor<string, []>("op_346_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_348 = const()[name = tensor<string, []>("op_348"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_148 = transpose(perm = var_346_perm_0, x = var_345_cast)[name = tensor<string, []>("transpose_148")]; |
| tensor<fp16, [20, 77, 64]> query_states_5_cast = reshape(shape = var_348, x = transpose_148)[name = tensor<string, []>("query_states_5_cast")]; |
| tensor<int32, [3]> var_350 = const()[name = tensor<string, []>("op_350"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_150 = transpose(perm = var_330_perm_0, x = var_329_cast)[name = tensor<string, []>("transpose_150")]; |
| tensor<fp16, [20, 77, 64]> key_states_11_cast = reshape(shape = var_350, x = transpose_150)[name = tensor<string, []>("key_states_11_cast")]; |
| tensor<int32, [3]> var_352 = const()[name = tensor<string, []>("op_352"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_149 = transpose(perm = var_337_perm_0, x = var_336_cast)[name = tensor<string, []>("transpose_149")]; |
| tensor<fp16, [20, 77, 64]> value_states_11_cast = reshape(shape = var_352, x = transpose_149)[name = tensor<string, []>("value_states_11_cast")]; |
| tensor<int32, [3]> var_355_perm_0 = const()[name = tensor<string, []>("op_355_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_13_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_13_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_13_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_13_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_147 = transpose(perm = var_355_perm_0, x = key_states_11_cast)[name = tensor<string, []>("transpose_147")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_13_cast = matmul(transpose_x = attn_weights_13_transpose_x_0, transpose_y = attn_weights_13_transpose_y_0, x = query_states_5_cast, y = transpose_147)[name = tensor<string, []>("attn_weights_13_cast")]; |
| tensor<int32, [4]> var_357 = const()[name = tensor<string, []>("op_357"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_358_cast = reshape(shape = var_357, x = attn_weights_13_cast)[name = tensor<string, []>("op_358_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_15_cast = add(x = var_358_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_15_cast")]; |
| tensor<int32, [3]> var_363 = const()[name = tensor<string, []>("op_363"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_37_cast = reshape(shape = var_363, x = attn_weights_15_cast)[name = tensor<string, []>("input_37_cast")]; |
| tensor<fp16, [20, 77, 77]> input_39_cast = softmax(axis = var_5, x = input_37_cast)[name = tensor<string, []>("input_39_cast")]; |
| 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 = matmul(transpose_x = attn_output_13_transpose_x_0, transpose_y = attn_output_13_transpose_y_0, x = input_39_cast, y = value_states_11_cast)[name = tensor<string, []>("attn_output_13_cast")]; |
| tensor<int32, [4]> var_368 = const()[name = tensor<string, []>("op_368"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_15_cast = reshape(shape = var_368, x = attn_output_13_cast)[name = tensor<string, []>("attn_output_15_cast")]; |
| 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_371 = const()[name = tensor<string, []>("op_371"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_146 = transpose(perm = attn_output_17_perm_0, x = attn_output_15_cast)[name = tensor<string, []>("transpose_146")]; |
| tensor<fp16, [1, 77, 1280]> input_41_cast = reshape(shape = var_371, x = transpose_146)[name = tensor<string, []>("input_41_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215249280)))]; |
| 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, []>(218526144)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_15_cast = 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, x = input_41_cast)[name = tensor<string, []>("hidden_states_15_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_43_cast = add(x = input_35_cast, y = hidden_states_15_cast)[name = tensor<string, []>("input_43_cast")]; |
| 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, []>(218528768)))]; |
| 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, []>(218531392)))]; |
| tensor<fp16, [1, 77, 1280]> input_45_cast = 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)[name = tensor<string, []>("input_45_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(218534016)))]; |
| 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, []>(231641280)))]; |
| tensor<fp16, [1, 77, 5120]> input_47_cast = 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, x = input_45_cast)[name = tensor<string, []>("input_47_cast")]; |
| 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 = gelu(mode = input_49_mode_0, x = input_47_cast)[name = tensor<string, []>("input_49_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(231651584)))]; |
| 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, []>(244758848)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_17_cast = 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, x = input_49_cast)[name = tensor<string, []>("hidden_states_17_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_51_cast = add(x = input_43_cast, y = hidden_states_17_cast)[name = tensor<string, []>("input_51_cast")]; |
| 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, []>(244761472)))]; |
| 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, []>(244764096)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_19_cast = 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)[name = tensor<string, []>("hidden_states_19_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244766720)))]; |
| 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, []>(248043584)))]; |
| tensor<fp16, [1, 77, 1280]> var_409_cast = 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, x = hidden_states_19_cast)[name = tensor<string, []>("op_409_cast")]; |
| tensor<fp16, []> var_410_to_fp16 = const()[name = tensor<string, []>("op_410_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_23_cast = mul(x = var_409_cast, y = var_410_to_fp16)[name = tensor<string, []>("tensor_23_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(248046208)))]; |
| 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, []>(251323072)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_19_cast = 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, x = hidden_states_19_cast)[name = tensor<string, []>("tensor_19_cast")]; |
| tensor<int32, [4]> var_415 = const()[name = tensor<string, []>("op_415"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_416_cast = reshape(shape = var_415, x = tensor_19_cast)[name = tensor<string, []>("op_416_cast")]; |
| tensor<int32, [4]> var_417_perm_0 = const()[name = tensor<string, []>("op_417_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(251325696)))]; |
| 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, []>(254602560)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_21_cast = 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, x = hidden_states_19_cast)[name = tensor<string, []>("tensor_21_cast")]; |
| tensor<int32, [4]> var_422 = const()[name = tensor<string, []>("op_422"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_423_cast = reshape(shape = var_422, x = tensor_21_cast)[name = tensor<string, []>("op_423_cast")]; |
| tensor<int32, [4]> var_424_perm_0 = const()[name = tensor<string, []>("op_424_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_431 = const()[name = tensor<string, []>("op_431"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_432_cast = reshape(shape = var_431, x = tensor_23_cast)[name = tensor<string, []>("op_432_cast")]; |
| tensor<int32, [4]> var_433_perm_0 = const()[name = tensor<string, []>("op_433_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_435 = const()[name = tensor<string, []>("op_435"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_143 = transpose(perm = var_433_perm_0, x = var_432_cast)[name = tensor<string, []>("transpose_143")]; |
| tensor<fp16, [20, 77, 64]> query_states_7_cast = reshape(shape = var_435, x = transpose_143)[name = tensor<string, []>("query_states_7_cast")]; |
| tensor<int32, [3]> var_437 = const()[name = tensor<string, []>("op_437"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_145 = transpose(perm = var_417_perm_0, x = var_416_cast)[name = tensor<string, []>("transpose_145")]; |
| tensor<fp16, [20, 77, 64]> key_states_15_cast = reshape(shape = var_437, x = transpose_145)[name = tensor<string, []>("key_states_15_cast")]; |
| tensor<int32, [3]> var_439 = const()[name = tensor<string, []>("op_439"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_144 = transpose(perm = var_424_perm_0, x = var_423_cast)[name = tensor<string, []>("transpose_144")]; |
| tensor<fp16, [20, 77, 64]> value_states_15_cast = reshape(shape = var_439, x = transpose_144)[name = tensor<string, []>("value_states_15_cast")]; |
| tensor<int32, [3]> var_442_perm_0 = const()[name = tensor<string, []>("op_442_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_19_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_19_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_19_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_19_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_142 = transpose(perm = var_442_perm_0, x = key_states_15_cast)[name = tensor<string, []>("transpose_142")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_19_cast = matmul(transpose_x = attn_weights_19_transpose_x_0, transpose_y = attn_weights_19_transpose_y_0, x = query_states_7_cast, y = transpose_142)[name = tensor<string, []>("attn_weights_19_cast")]; |
| tensor<int32, [4]> var_444 = const()[name = tensor<string, []>("op_444"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_445_cast = reshape(shape = var_444, x = attn_weights_19_cast)[name = tensor<string, []>("op_445_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_21_cast = add(x = var_445_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_21_cast")]; |
| tensor<int32, [3]> var_450 = const()[name = tensor<string, []>("op_450"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_53_cast = reshape(shape = var_450, x = attn_weights_21_cast)[name = tensor<string, []>("input_53_cast")]; |
| tensor<fp16, [20, 77, 77]> input_55_cast = softmax(axis = var_5, x = input_53_cast)[name = tensor<string, []>("input_55_cast")]; |
| 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 = matmul(transpose_x = attn_output_19_transpose_x_0, transpose_y = attn_output_19_transpose_y_0, x = input_55_cast, y = value_states_15_cast)[name = tensor<string, []>("attn_output_19_cast")]; |
| tensor<int32, [4]> var_455 = const()[name = tensor<string, []>("op_455"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_21_cast = reshape(shape = var_455, x = attn_output_19_cast)[name = tensor<string, []>("attn_output_21_cast")]; |
| 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_458 = const()[name = tensor<string, []>("op_458"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_141 = transpose(perm = attn_output_23_perm_0, x = attn_output_21_cast)[name = tensor<string, []>("transpose_141")]; |
| tensor<fp16, [1, 77, 1280]> input_57_cast = reshape(shape = var_458, x = transpose_141)[name = tensor<string, []>("input_57_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(254605184)))]; |
| 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, []>(257882048)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_21_cast = 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, x = input_57_cast)[name = tensor<string, []>("hidden_states_21_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_59_cast = add(x = input_51_cast, y = hidden_states_21_cast)[name = tensor<string, []>("input_59_cast")]; |
| 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, []>(257884672)))]; |
| 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, []>(257887296)))]; |
| tensor<fp16, [1, 77, 1280]> input_61_cast = 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)[name = tensor<string, []>("input_61_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(257889920)))]; |
| 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, []>(270997184)))]; |
| tensor<fp16, [1, 77, 5120]> input_63_cast = 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, x = input_61_cast)[name = tensor<string, []>("input_63_cast")]; |
| 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 = gelu(mode = input_65_mode_0, x = input_63_cast)[name = tensor<string, []>("input_65_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(271007488)))]; |
| 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, []>(284114752)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_23_cast = 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, x = input_65_cast)[name = tensor<string, []>("hidden_states_23_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_67_cast = add(x = input_59_cast, y = hidden_states_23_cast)[name = tensor<string, []>("input_67_cast")]; |
| 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, []>(284117376)))]; |
| 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, []>(284120000)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_25_cast = 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)[name = tensor<string, []>("hidden_states_25_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284122624)))]; |
| 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, []>(287399488)))]; |
| tensor<fp16, [1, 77, 1280]> var_496_cast = 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, x = hidden_states_25_cast)[name = tensor<string, []>("op_496_cast")]; |
| tensor<fp16, []> var_497_to_fp16 = const()[name = tensor<string, []>("op_497_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_29_cast = mul(x = var_496_cast, y = var_497_to_fp16)[name = tensor<string, []>("tensor_29_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(287402112)))]; |
| 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, []>(290678976)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_25_cast = 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, x = hidden_states_25_cast)[name = tensor<string, []>("tensor_25_cast")]; |
| tensor<int32, [4]> var_502 = const()[name = tensor<string, []>("op_502"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_503_cast = reshape(shape = var_502, x = tensor_25_cast)[name = tensor<string, []>("op_503_cast")]; |
| tensor<int32, [4]> var_504_perm_0 = const()[name = tensor<string, []>("op_504_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(290681600)))]; |
| 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, []>(293958464)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_27_cast = 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, x = hidden_states_25_cast)[name = tensor<string, []>("tensor_27_cast")]; |
| tensor<int32, [4]> var_509 = const()[name = tensor<string, []>("op_509"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_510_cast = reshape(shape = var_509, x = tensor_27_cast)[name = tensor<string, []>("op_510_cast")]; |
| tensor<int32, [4]> var_511_perm_0 = const()[name = tensor<string, []>("op_511_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_518 = const()[name = tensor<string, []>("op_518"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_519_cast = reshape(shape = var_518, x = tensor_29_cast)[name = tensor<string, []>("op_519_cast")]; |
| tensor<int32, [4]> var_520_perm_0 = const()[name = tensor<string, []>("op_520_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_522 = const()[name = tensor<string, []>("op_522"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_138 = transpose(perm = var_520_perm_0, x = var_519_cast)[name = tensor<string, []>("transpose_138")]; |
| tensor<fp16, [20, 77, 64]> query_states_9_cast = reshape(shape = var_522, x = transpose_138)[name = tensor<string, []>("query_states_9_cast")]; |
| tensor<int32, [3]> var_524 = const()[name = tensor<string, []>("op_524"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_140 = transpose(perm = var_504_perm_0, x = var_503_cast)[name = tensor<string, []>("transpose_140")]; |
| tensor<fp16, [20, 77, 64]> key_states_19_cast = reshape(shape = var_524, x = transpose_140)[name = tensor<string, []>("key_states_19_cast")]; |
| tensor<int32, [3]> var_526 = const()[name = tensor<string, []>("op_526"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_139 = transpose(perm = var_511_perm_0, x = var_510_cast)[name = tensor<string, []>("transpose_139")]; |
| tensor<fp16, [20, 77, 64]> value_states_19_cast = reshape(shape = var_526, x = transpose_139)[name = tensor<string, []>("value_states_19_cast")]; |
| tensor<int32, [3]> var_529_perm_0 = const()[name = tensor<string, []>("op_529_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_25_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_25_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_25_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_25_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_137 = transpose(perm = var_529_perm_0, x = key_states_19_cast)[name = tensor<string, []>("transpose_137")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_25_cast = matmul(transpose_x = attn_weights_25_transpose_x_0, transpose_y = attn_weights_25_transpose_y_0, x = query_states_9_cast, y = transpose_137)[name = tensor<string, []>("attn_weights_25_cast")]; |
| tensor<int32, [4]> var_531 = const()[name = tensor<string, []>("op_531"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_532_cast = reshape(shape = var_531, x = attn_weights_25_cast)[name = tensor<string, []>("op_532_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_27_cast = add(x = var_532_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_27_cast")]; |
| tensor<int32, [3]> var_537 = const()[name = tensor<string, []>("op_537"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_69_cast = reshape(shape = var_537, x = attn_weights_27_cast)[name = tensor<string, []>("input_69_cast")]; |
| tensor<fp16, [20, 77, 77]> input_71_cast = softmax(axis = var_5, x = input_69_cast)[name = tensor<string, []>("input_71_cast")]; |
| 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 = matmul(transpose_x = attn_output_25_transpose_x_0, transpose_y = attn_output_25_transpose_y_0, x = input_71_cast, y = value_states_19_cast)[name = tensor<string, []>("attn_output_25_cast")]; |
| tensor<int32, [4]> var_542 = const()[name = tensor<string, []>("op_542"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_27_cast = reshape(shape = var_542, x = attn_output_25_cast)[name = tensor<string, []>("attn_output_27_cast")]; |
| 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_545 = const()[name = tensor<string, []>("op_545"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_136 = transpose(perm = attn_output_29_perm_0, x = attn_output_27_cast)[name = tensor<string, []>("transpose_136")]; |
| tensor<fp16, [1, 77, 1280]> input_73_cast = reshape(shape = var_545, x = transpose_136)[name = tensor<string, []>("input_73_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(293961088)))]; |
| 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, []>(297237952)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_27_cast = 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, x = input_73_cast)[name = tensor<string, []>("hidden_states_27_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_75_cast = add(x = input_67_cast, y = hidden_states_27_cast)[name = tensor<string, []>("input_75_cast")]; |
| 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, []>(297240576)))]; |
| 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, []>(297243200)))]; |
| tensor<fp16, [1, 77, 1280]> input_77_cast = 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)[name = tensor<string, []>("input_77_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(297245824)))]; |
| 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, []>(310353088)))]; |
| tensor<fp16, [1, 77, 5120]> input_79_cast = 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, x = input_77_cast)[name = tensor<string, []>("input_79_cast")]; |
| 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 = gelu(mode = input_81_mode_0, x = input_79_cast)[name = tensor<string, []>("input_81_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(310363392)))]; |
| 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, []>(323470656)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_29_cast = 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, x = input_81_cast)[name = tensor<string, []>("hidden_states_29_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_83_cast = add(x = input_75_cast, y = hidden_states_29_cast)[name = tensor<string, []>("input_83_cast")]; |
| 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, []>(323473280)))]; |
| 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, []>(323475904)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_31_cast = 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)[name = tensor<string, []>("hidden_states_31_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(323478528)))]; |
| 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, []>(326755392)))]; |
| tensor<fp16, [1, 77, 1280]> var_583_cast = 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, x = hidden_states_31_cast)[name = tensor<string, []>("op_583_cast")]; |
| tensor<fp16, []> var_584_to_fp16 = const()[name = tensor<string, []>("op_584_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_35_cast = mul(x = var_583_cast, y = var_584_to_fp16)[name = tensor<string, []>("tensor_35_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(326758016)))]; |
| 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, []>(330034880)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_31_cast = 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, x = hidden_states_31_cast)[name = tensor<string, []>("tensor_31_cast")]; |
| tensor<int32, [4]> var_589 = const()[name = tensor<string, []>("op_589"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_590_cast = reshape(shape = var_589, x = tensor_31_cast)[name = tensor<string, []>("op_590_cast")]; |
| tensor<int32, [4]> var_591_perm_0 = const()[name = tensor<string, []>("op_591_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(330037504)))]; |
| 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, []>(333314368)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_33_cast = 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, x = hidden_states_31_cast)[name = tensor<string, []>("tensor_33_cast")]; |
| tensor<int32, [4]> var_596 = const()[name = tensor<string, []>("op_596"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_597_cast = reshape(shape = var_596, x = tensor_33_cast)[name = tensor<string, []>("op_597_cast")]; |
| tensor<int32, [4]> var_598_perm_0 = const()[name = tensor<string, []>("op_598_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_605 = const()[name = tensor<string, []>("op_605"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_606_cast = reshape(shape = var_605, x = tensor_35_cast)[name = tensor<string, []>("op_606_cast")]; |
| tensor<int32, [4]> var_607_perm_0 = const()[name = tensor<string, []>("op_607_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_609 = const()[name = tensor<string, []>("op_609"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_133 = transpose(perm = var_607_perm_0, x = var_606_cast)[name = tensor<string, []>("transpose_133")]; |
| tensor<fp16, [20, 77, 64]> query_states_11_cast = reshape(shape = var_609, x = transpose_133)[name = tensor<string, []>("query_states_11_cast")]; |
| tensor<int32, [3]> var_611 = const()[name = tensor<string, []>("op_611"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_135 = transpose(perm = var_591_perm_0, x = var_590_cast)[name = tensor<string, []>("transpose_135")]; |
| tensor<fp16, [20, 77, 64]> key_states_23_cast = reshape(shape = var_611, x = transpose_135)[name = tensor<string, []>("key_states_23_cast")]; |
| tensor<int32, [3]> var_613 = const()[name = tensor<string, []>("op_613"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_134 = transpose(perm = var_598_perm_0, x = var_597_cast)[name = tensor<string, []>("transpose_134")]; |
| tensor<fp16, [20, 77, 64]> value_states_23_cast = reshape(shape = var_613, x = transpose_134)[name = tensor<string, []>("value_states_23_cast")]; |
| tensor<int32, [3]> var_616_perm_0 = const()[name = tensor<string, []>("op_616_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_31_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_31_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_31_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_31_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_132 = transpose(perm = var_616_perm_0, x = key_states_23_cast)[name = tensor<string, []>("transpose_132")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_31_cast = matmul(transpose_x = attn_weights_31_transpose_x_0, transpose_y = attn_weights_31_transpose_y_0, x = query_states_11_cast, y = transpose_132)[name = tensor<string, []>("attn_weights_31_cast")]; |
| tensor<int32, [4]> var_618 = const()[name = tensor<string, []>("op_618"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_619_cast = reshape(shape = var_618, x = attn_weights_31_cast)[name = tensor<string, []>("op_619_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_33_cast = add(x = var_619_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_33_cast")]; |
| tensor<int32, [3]> var_624 = const()[name = tensor<string, []>("op_624"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_85_cast = reshape(shape = var_624, x = attn_weights_33_cast)[name = tensor<string, []>("input_85_cast")]; |
| tensor<fp16, [20, 77, 77]> input_87_cast = softmax(axis = var_5, x = input_85_cast)[name = tensor<string, []>("input_87_cast")]; |
| 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 = matmul(transpose_x = attn_output_31_transpose_x_0, transpose_y = attn_output_31_transpose_y_0, x = input_87_cast, y = value_states_23_cast)[name = tensor<string, []>("attn_output_31_cast")]; |
| tensor<int32, [4]> var_629 = const()[name = tensor<string, []>("op_629"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_33_cast = reshape(shape = var_629, x = attn_output_31_cast)[name = tensor<string, []>("attn_output_33_cast")]; |
| 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_632 = const()[name = tensor<string, []>("op_632"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_131 = transpose(perm = attn_output_35_perm_0, x = attn_output_33_cast)[name = tensor<string, []>("transpose_131")]; |
| tensor<fp16, [1, 77, 1280]> input_89_cast = reshape(shape = var_632, x = transpose_131)[name = tensor<string, []>("input_89_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(333316992)))]; |
| 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, []>(336593856)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_33_cast = 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, x = input_89_cast)[name = tensor<string, []>("hidden_states_33_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_91_cast = add(x = input_83_cast, y = hidden_states_33_cast)[name = tensor<string, []>("input_91_cast")]; |
| 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, []>(336596480)))]; |
| 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, []>(336599104)))]; |
| tensor<fp16, [1, 77, 1280]> input_93_cast = 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)[name = tensor<string, []>("input_93_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(336601728)))]; |
| 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, []>(349708992)))]; |
| tensor<fp16, [1, 77, 5120]> input_95_cast = 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, x = input_93_cast)[name = tensor<string, []>("input_95_cast")]; |
| 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 = gelu(mode = input_97_mode_0, x = input_95_cast)[name = tensor<string, []>("input_97_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(349719296)))]; |
| 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, []>(362826560)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_35_cast = 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, x = input_97_cast)[name = tensor<string, []>("hidden_states_35_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_99_cast = add(x = input_91_cast, y = hidden_states_35_cast)[name = tensor<string, []>("input_99_cast")]; |
| 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, []>(362829184)))]; |
| 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, []>(362831808)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_37_cast = 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)[name = tensor<string, []>("hidden_states_37_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(362834432)))]; |
| 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, []>(366111296)))]; |
| tensor<fp16, [1, 77, 1280]> var_670_cast = 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, x = hidden_states_37_cast)[name = tensor<string, []>("op_670_cast")]; |
| tensor<fp16, []> var_671_to_fp16 = const()[name = tensor<string, []>("op_671_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_41_cast = mul(x = var_670_cast, y = var_671_to_fp16)[name = tensor<string, []>("tensor_41_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(366113920)))]; |
| 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, []>(369390784)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_37_cast = 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, x = hidden_states_37_cast)[name = tensor<string, []>("tensor_37_cast")]; |
| tensor<int32, [4]> var_676 = const()[name = tensor<string, []>("op_676"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_677_cast = reshape(shape = var_676, x = tensor_37_cast)[name = tensor<string, []>("op_677_cast")]; |
| tensor<int32, [4]> var_678_perm_0 = const()[name = tensor<string, []>("op_678_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(369393408)))]; |
| 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, []>(372670272)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_39_cast = 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, x = hidden_states_37_cast)[name = tensor<string, []>("tensor_39_cast")]; |
| tensor<int32, [4]> var_683 = const()[name = tensor<string, []>("op_683"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_684_cast = reshape(shape = var_683, x = tensor_39_cast)[name = tensor<string, []>("op_684_cast")]; |
| tensor<int32, [4]> var_685_perm_0 = const()[name = tensor<string, []>("op_685_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_692 = const()[name = tensor<string, []>("op_692"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_693_cast = reshape(shape = var_692, x = tensor_41_cast)[name = tensor<string, []>("op_693_cast")]; |
| tensor<int32, [4]> var_694_perm_0 = const()[name = tensor<string, []>("op_694_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_696 = const()[name = tensor<string, []>("op_696"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_128 = transpose(perm = var_694_perm_0, x = var_693_cast)[name = tensor<string, []>("transpose_128")]; |
| tensor<fp16, [20, 77, 64]> query_states_13_cast = reshape(shape = var_696, x = transpose_128)[name = tensor<string, []>("query_states_13_cast")]; |
| tensor<int32, [3]> var_698 = const()[name = tensor<string, []>("op_698"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_130 = transpose(perm = var_678_perm_0, x = var_677_cast)[name = tensor<string, []>("transpose_130")]; |
| tensor<fp16, [20, 77, 64]> key_states_27_cast = reshape(shape = var_698, x = transpose_130)[name = tensor<string, []>("key_states_27_cast")]; |
| tensor<int32, [3]> var_700 = const()[name = tensor<string, []>("op_700"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_129 = transpose(perm = var_685_perm_0, x = var_684_cast)[name = tensor<string, []>("transpose_129")]; |
| tensor<fp16, [20, 77, 64]> value_states_27_cast = reshape(shape = var_700, x = transpose_129)[name = tensor<string, []>("value_states_27_cast")]; |
| tensor<int32, [3]> var_703_perm_0 = const()[name = tensor<string, []>("op_703_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_37_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_37_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_37_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_37_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_127 = transpose(perm = var_703_perm_0, x = key_states_27_cast)[name = tensor<string, []>("transpose_127")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_37_cast = matmul(transpose_x = attn_weights_37_transpose_x_0, transpose_y = attn_weights_37_transpose_y_0, x = query_states_13_cast, y = transpose_127)[name = tensor<string, []>("attn_weights_37_cast")]; |
| tensor<int32, [4]> var_705 = const()[name = tensor<string, []>("op_705"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_706_cast = reshape(shape = var_705, x = attn_weights_37_cast)[name = tensor<string, []>("op_706_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_39_cast = add(x = var_706_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_39_cast")]; |
| tensor<int32, [3]> var_711 = const()[name = tensor<string, []>("op_711"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_101_cast = reshape(shape = var_711, x = attn_weights_39_cast)[name = tensor<string, []>("input_101_cast")]; |
| tensor<fp16, [20, 77, 77]> input_103_cast = softmax(axis = var_5, x = input_101_cast)[name = tensor<string, []>("input_103_cast")]; |
| 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 = matmul(transpose_x = attn_output_37_transpose_x_0, transpose_y = attn_output_37_transpose_y_0, x = input_103_cast, y = value_states_27_cast)[name = tensor<string, []>("attn_output_37_cast")]; |
| tensor<int32, [4]> var_716 = const()[name = tensor<string, []>("op_716"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_39_cast = reshape(shape = var_716, x = attn_output_37_cast)[name = tensor<string, []>("attn_output_39_cast")]; |
| 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_719 = const()[name = tensor<string, []>("op_719"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_126 = transpose(perm = attn_output_41_perm_0, x = attn_output_39_cast)[name = tensor<string, []>("transpose_126")]; |
| tensor<fp16, [1, 77, 1280]> input_105_cast = reshape(shape = var_719, x = transpose_126)[name = tensor<string, []>("input_105_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(372672896)))]; |
| 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, []>(375949760)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_39_cast = 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, x = input_105_cast)[name = tensor<string, []>("hidden_states_39_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_107_cast = add(x = input_99_cast, y = hidden_states_39_cast)[name = tensor<string, []>("input_107_cast")]; |
| 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, []>(375952384)))]; |
| 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, []>(375955008)))]; |
| tensor<fp16, [1, 77, 1280]> input_109_cast = 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)[name = tensor<string, []>("input_109_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(375957632)))]; |
| 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, []>(389064896)))]; |
| tensor<fp16, [1, 77, 5120]> input_111_cast = 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, x = input_109_cast)[name = tensor<string, []>("input_111_cast")]; |
| 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 = gelu(mode = input_113_mode_0, x = input_111_cast)[name = tensor<string, []>("input_113_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(389075200)))]; |
| 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, []>(402182464)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_41_cast = 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, x = input_113_cast)[name = tensor<string, []>("hidden_states_41_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_115_cast = add(x = input_107_cast, y = hidden_states_41_cast)[name = tensor<string, []>("input_115_cast")]; |
| 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, []>(402185088)))]; |
| 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, []>(402187712)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_43_cast = 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)[name = tensor<string, []>("hidden_states_43_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(402190336)))]; |
| 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, []>(405467200)))]; |
| tensor<fp16, [1, 77, 1280]> var_757_cast = 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, x = hidden_states_43_cast)[name = tensor<string, []>("op_757_cast")]; |
| tensor<fp16, []> var_758_to_fp16 = const()[name = tensor<string, []>("op_758_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_47_cast = mul(x = var_757_cast, y = var_758_to_fp16)[name = tensor<string, []>("tensor_47_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(405469824)))]; |
| 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, []>(408746688)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_43_cast = 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, x = hidden_states_43_cast)[name = tensor<string, []>("tensor_43_cast")]; |
| tensor<int32, [4]> var_763 = const()[name = tensor<string, []>("op_763"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_764_cast = reshape(shape = var_763, x = tensor_43_cast)[name = tensor<string, []>("op_764_cast")]; |
| tensor<int32, [4]> var_765_perm_0 = const()[name = tensor<string, []>("op_765_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(408749312)))]; |
| 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, []>(412026176)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_45_cast = 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, x = hidden_states_43_cast)[name = tensor<string, []>("tensor_45_cast")]; |
| tensor<int32, [4]> var_770 = const()[name = tensor<string, []>("op_770"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_771_cast = reshape(shape = var_770, x = tensor_45_cast)[name = tensor<string, []>("op_771_cast")]; |
| tensor<int32, [4]> var_772_perm_0 = const()[name = tensor<string, []>("op_772_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_779 = const()[name = tensor<string, []>("op_779"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_780_cast = reshape(shape = var_779, x = tensor_47_cast)[name = tensor<string, []>("op_780_cast")]; |
| tensor<int32, [4]> var_781_perm_0 = const()[name = tensor<string, []>("op_781_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_783 = const()[name = tensor<string, []>("op_783"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_123 = transpose(perm = var_781_perm_0, x = var_780_cast)[name = tensor<string, []>("transpose_123")]; |
| tensor<fp16, [20, 77, 64]> query_states_15_cast = reshape(shape = var_783, x = transpose_123)[name = tensor<string, []>("query_states_15_cast")]; |
| tensor<int32, [3]> var_785 = const()[name = tensor<string, []>("op_785"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_125 = transpose(perm = var_765_perm_0, x = var_764_cast)[name = tensor<string, []>("transpose_125")]; |
| tensor<fp16, [20, 77, 64]> key_states_31_cast = reshape(shape = var_785, x = transpose_125)[name = tensor<string, []>("key_states_31_cast")]; |
| tensor<int32, [3]> var_787 = const()[name = tensor<string, []>("op_787"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_124 = transpose(perm = var_772_perm_0, x = var_771_cast)[name = tensor<string, []>("transpose_124")]; |
| tensor<fp16, [20, 77, 64]> value_states_31_cast = reshape(shape = var_787, x = transpose_124)[name = tensor<string, []>("value_states_31_cast")]; |
| tensor<int32, [3]> var_790_perm_0 = const()[name = tensor<string, []>("op_790_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_43_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_43_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_43_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_43_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_122 = transpose(perm = var_790_perm_0, x = key_states_31_cast)[name = tensor<string, []>("transpose_122")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_43_cast = matmul(transpose_x = attn_weights_43_transpose_x_0, transpose_y = attn_weights_43_transpose_y_0, x = query_states_15_cast, y = transpose_122)[name = tensor<string, []>("attn_weights_43_cast")]; |
| tensor<int32, [4]> var_792 = const()[name = tensor<string, []>("op_792"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_793_cast = reshape(shape = var_792, x = attn_weights_43_cast)[name = tensor<string, []>("op_793_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_45_cast = add(x = var_793_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_45_cast")]; |
| tensor<int32, [3]> var_798 = const()[name = tensor<string, []>("op_798"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_117_cast = reshape(shape = var_798, x = attn_weights_45_cast)[name = tensor<string, []>("input_117_cast")]; |
| tensor<fp16, [20, 77, 77]> input_119_cast = softmax(axis = var_5, x = input_117_cast)[name = tensor<string, []>("input_119_cast")]; |
| 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 = matmul(transpose_x = attn_output_43_transpose_x_0, transpose_y = attn_output_43_transpose_y_0, x = input_119_cast, y = value_states_31_cast)[name = tensor<string, []>("attn_output_43_cast")]; |
| tensor<int32, [4]> var_803 = const()[name = tensor<string, []>("op_803"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_45_cast = reshape(shape = var_803, x = attn_output_43_cast)[name = tensor<string, []>("attn_output_45_cast")]; |
| 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_806 = const()[name = tensor<string, []>("op_806"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_121 = transpose(perm = attn_output_47_perm_0, x = attn_output_45_cast)[name = tensor<string, []>("transpose_121")]; |
| tensor<fp16, [1, 77, 1280]> input_121_cast = reshape(shape = var_806, x = transpose_121)[name = tensor<string, []>("input_121_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(412028800)))]; |
| 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, []>(415305664)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_45_cast = 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, x = input_121_cast)[name = tensor<string, []>("hidden_states_45_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_123_cast = add(x = input_115_cast, y = hidden_states_45_cast)[name = tensor<string, []>("input_123_cast")]; |
| 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, []>(415308288)))]; |
| 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, []>(415310912)))]; |
| tensor<fp16, [1, 77, 1280]> input_125_cast = 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)[name = tensor<string, []>("input_125_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(415313536)))]; |
| 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, []>(428420800)))]; |
| tensor<fp16, [1, 77, 5120]> input_127_cast = 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, x = input_125_cast)[name = tensor<string, []>("input_127_cast")]; |
| 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 = gelu(mode = input_129_mode_0, x = input_127_cast)[name = tensor<string, []>("input_129_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(428431104)))]; |
| 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, []>(441538368)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_47_cast = 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, x = input_129_cast)[name = tensor<string, []>("hidden_states_47_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_131_cast = add(x = input_123_cast, y = hidden_states_47_cast)[name = tensor<string, []>("input_131_cast")]; |
| 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, []>(441540992)))]; |
| 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, []>(441543616)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_49_cast = 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)[name = tensor<string, []>("hidden_states_49_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441546240)))]; |
| 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, []>(444823104)))]; |
| tensor<fp16, [1, 77, 1280]> var_844_cast = 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, x = hidden_states_49_cast)[name = tensor<string, []>("op_844_cast")]; |
| tensor<fp16, []> var_845_to_fp16 = const()[name = tensor<string, []>("op_845_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_53_cast = mul(x = var_844_cast, y = var_845_to_fp16)[name = tensor<string, []>("tensor_53_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(444825728)))]; |
| 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, []>(448102592)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_49_cast = 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, x = hidden_states_49_cast)[name = tensor<string, []>("tensor_49_cast")]; |
| tensor<int32, [4]> var_850 = const()[name = tensor<string, []>("op_850"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_851_cast = reshape(shape = var_850, x = tensor_49_cast)[name = tensor<string, []>("op_851_cast")]; |
| tensor<int32, [4]> var_852_perm_0 = const()[name = tensor<string, []>("op_852_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(448105216)))]; |
| 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, []>(451382080)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_51_cast = 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, x = hidden_states_49_cast)[name = tensor<string, []>("tensor_51_cast")]; |
| tensor<int32, [4]> var_857 = const()[name = tensor<string, []>("op_857"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_858_cast = reshape(shape = var_857, x = tensor_51_cast)[name = tensor<string, []>("op_858_cast")]; |
| tensor<int32, [4]> var_859_perm_0 = const()[name = tensor<string, []>("op_859_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_866 = const()[name = tensor<string, []>("op_866"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_867_cast = reshape(shape = var_866, x = tensor_53_cast)[name = tensor<string, []>("op_867_cast")]; |
| tensor<int32, [4]> var_868_perm_0 = const()[name = tensor<string, []>("op_868_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_870 = const()[name = tensor<string, []>("op_870"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_118 = transpose(perm = var_868_perm_0, x = var_867_cast)[name = tensor<string, []>("transpose_118")]; |
| tensor<fp16, [20, 77, 64]> query_states_17_cast = reshape(shape = var_870, x = transpose_118)[name = tensor<string, []>("query_states_17_cast")]; |
| tensor<int32, [3]> var_872 = const()[name = tensor<string, []>("op_872"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_120 = transpose(perm = var_852_perm_0, x = var_851_cast)[name = tensor<string, []>("transpose_120")]; |
| tensor<fp16, [20, 77, 64]> key_states_35_cast = reshape(shape = var_872, x = transpose_120)[name = tensor<string, []>("key_states_35_cast")]; |
| tensor<int32, [3]> var_874 = const()[name = tensor<string, []>("op_874"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_119 = transpose(perm = var_859_perm_0, x = var_858_cast)[name = tensor<string, []>("transpose_119")]; |
| tensor<fp16, [20, 77, 64]> value_states_35_cast = reshape(shape = var_874, x = transpose_119)[name = tensor<string, []>("value_states_35_cast")]; |
| tensor<int32, [3]> var_877_perm_0 = const()[name = tensor<string, []>("op_877_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_49_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_49_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_49_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_49_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_117 = transpose(perm = var_877_perm_0, x = key_states_35_cast)[name = tensor<string, []>("transpose_117")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_49_cast = matmul(transpose_x = attn_weights_49_transpose_x_0, transpose_y = attn_weights_49_transpose_y_0, x = query_states_17_cast, y = transpose_117)[name = tensor<string, []>("attn_weights_49_cast")]; |
| tensor<int32, [4]> var_879 = const()[name = tensor<string, []>("op_879"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_880_cast = reshape(shape = var_879, x = attn_weights_49_cast)[name = tensor<string, []>("op_880_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_51_cast = add(x = var_880_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_51_cast")]; |
| tensor<int32, [3]> var_885 = const()[name = tensor<string, []>("op_885"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_133_cast = reshape(shape = var_885, x = attn_weights_51_cast)[name = tensor<string, []>("input_133_cast")]; |
| tensor<fp16, [20, 77, 77]> input_135_cast = softmax(axis = var_5, x = input_133_cast)[name = tensor<string, []>("input_135_cast")]; |
| 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 = matmul(transpose_x = attn_output_49_transpose_x_0, transpose_y = attn_output_49_transpose_y_0, x = input_135_cast, y = value_states_35_cast)[name = tensor<string, []>("attn_output_49_cast")]; |
| tensor<int32, [4]> var_890 = const()[name = tensor<string, []>("op_890"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_51_cast = reshape(shape = var_890, x = attn_output_49_cast)[name = tensor<string, []>("attn_output_51_cast")]; |
| 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_893 = const()[name = tensor<string, []>("op_893"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_116 = transpose(perm = attn_output_53_perm_0, x = attn_output_51_cast)[name = tensor<string, []>("transpose_116")]; |
| tensor<fp16, [1, 77, 1280]> input_137_cast = reshape(shape = var_893, x = transpose_116)[name = tensor<string, []>("input_137_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(451384704)))]; |
| 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, []>(454661568)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_51_cast = 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, x = input_137_cast)[name = tensor<string, []>("hidden_states_51_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_139_cast = add(x = input_131_cast, y = hidden_states_51_cast)[name = tensor<string, []>("input_139_cast")]; |
| 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, []>(454664192)))]; |
| 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, []>(454666816)))]; |
| tensor<fp16, [1, 77, 1280]> input_141_cast = 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)[name = tensor<string, []>("input_141_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(454669440)))]; |
| 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, []>(467776704)))]; |
| tensor<fp16, [1, 77, 5120]> input_143_cast = 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, x = input_141_cast)[name = tensor<string, []>("input_143_cast")]; |
| 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 = gelu(mode = input_145_mode_0, x = input_143_cast)[name = tensor<string, []>("input_145_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(467787008)))]; |
| 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, []>(480894272)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_53_cast = 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, x = input_145_cast)[name = tensor<string, []>("hidden_states_53_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_147_cast = add(x = input_139_cast, y = hidden_states_53_cast)[name = tensor<string, []>("input_147_cast")]; |
| 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, []>(480896896)))]; |
| 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, []>(480899520)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_55_cast = 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)[name = tensor<string, []>("hidden_states_55_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(480902144)))]; |
| 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, []>(484179008)))]; |
| tensor<fp16, [1, 77, 1280]> var_931_cast = 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, x = hidden_states_55_cast)[name = tensor<string, []>("op_931_cast")]; |
| tensor<fp16, []> var_932_to_fp16 = const()[name = tensor<string, []>("op_932_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_59_cast = mul(x = var_931_cast, y = var_932_to_fp16)[name = tensor<string, []>("tensor_59_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(484181632)))]; |
| 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, []>(487458496)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_55_cast = 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, x = hidden_states_55_cast)[name = tensor<string, []>("tensor_55_cast")]; |
| tensor<int32, [4]> var_937 = const()[name = tensor<string, []>("op_937"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_938_cast = reshape(shape = var_937, x = tensor_55_cast)[name = tensor<string, []>("op_938_cast")]; |
| tensor<int32, [4]> var_939_perm_0 = const()[name = tensor<string, []>("op_939_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(487461120)))]; |
| 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, []>(490737984)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_57_cast = 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, x = hidden_states_55_cast)[name = tensor<string, []>("tensor_57_cast")]; |
| tensor<int32, [4]> var_944 = const()[name = tensor<string, []>("op_944"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_945_cast = reshape(shape = var_944, x = tensor_57_cast)[name = tensor<string, []>("op_945_cast")]; |
| tensor<int32, [4]> var_946_perm_0 = const()[name = tensor<string, []>("op_946_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_953 = const()[name = tensor<string, []>("op_953"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_954_cast = reshape(shape = var_953, x = tensor_59_cast)[name = tensor<string, []>("op_954_cast")]; |
| tensor<int32, [4]> var_955_perm_0 = const()[name = tensor<string, []>("op_955_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_957 = const()[name = tensor<string, []>("op_957"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_113 = transpose(perm = var_955_perm_0, x = var_954_cast)[name = tensor<string, []>("transpose_113")]; |
| tensor<fp16, [20, 77, 64]> query_states_19_cast = reshape(shape = var_957, x = transpose_113)[name = tensor<string, []>("query_states_19_cast")]; |
| tensor<int32, [3]> var_959 = const()[name = tensor<string, []>("op_959"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_115 = transpose(perm = var_939_perm_0, x = var_938_cast)[name = tensor<string, []>("transpose_115")]; |
| tensor<fp16, [20, 77, 64]> key_states_39_cast = reshape(shape = var_959, x = transpose_115)[name = tensor<string, []>("key_states_39_cast")]; |
| tensor<int32, [3]> var_961 = const()[name = tensor<string, []>("op_961"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_114 = transpose(perm = var_946_perm_0, x = var_945_cast)[name = tensor<string, []>("transpose_114")]; |
| tensor<fp16, [20, 77, 64]> value_states_39_cast = reshape(shape = var_961, x = transpose_114)[name = tensor<string, []>("value_states_39_cast")]; |
| tensor<int32, [3]> var_964_perm_0 = const()[name = tensor<string, []>("op_964_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_55_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_55_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_55_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_55_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_112 = transpose(perm = var_964_perm_0, x = key_states_39_cast)[name = tensor<string, []>("transpose_112")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_55_cast = matmul(transpose_x = attn_weights_55_transpose_x_0, transpose_y = attn_weights_55_transpose_y_0, x = query_states_19_cast, y = transpose_112)[name = tensor<string, []>("attn_weights_55_cast")]; |
| tensor<int32, [4]> var_966 = const()[name = tensor<string, []>("op_966"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_967_cast = reshape(shape = var_966, x = attn_weights_55_cast)[name = tensor<string, []>("op_967_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_57_cast = add(x = var_967_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_57_cast")]; |
| tensor<int32, [3]> var_972 = const()[name = tensor<string, []>("op_972"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_149_cast = reshape(shape = var_972, x = attn_weights_57_cast)[name = tensor<string, []>("input_149_cast")]; |
| tensor<fp16, [20, 77, 77]> input_151_cast = softmax(axis = var_5, x = input_149_cast)[name = tensor<string, []>("input_151_cast")]; |
| 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 = matmul(transpose_x = attn_output_55_transpose_x_0, transpose_y = attn_output_55_transpose_y_0, x = input_151_cast, y = value_states_39_cast)[name = tensor<string, []>("attn_output_55_cast")]; |
| tensor<int32, [4]> var_977 = const()[name = tensor<string, []>("op_977"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_57_cast = reshape(shape = var_977, x = attn_output_55_cast)[name = tensor<string, []>("attn_output_57_cast")]; |
| 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_980 = const()[name = tensor<string, []>("op_980"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_111 = transpose(perm = attn_output_59_perm_0, x = attn_output_57_cast)[name = tensor<string, []>("transpose_111")]; |
| tensor<fp16, [1, 77, 1280]> input_153_cast = reshape(shape = var_980, x = transpose_111)[name = tensor<string, []>("input_153_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(490740608)))]; |
| 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, []>(494017472)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_57_cast = 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, x = input_153_cast)[name = tensor<string, []>("hidden_states_57_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_155_cast = add(x = input_147_cast, y = hidden_states_57_cast)[name = tensor<string, []>("input_155_cast")]; |
| 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, []>(494020096)))]; |
| 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, []>(494022720)))]; |
| tensor<fp16, [1, 77, 1280]> input_157_cast = 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)[name = tensor<string, []>("input_157_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(494025344)))]; |
| 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, []>(507132608)))]; |
| tensor<fp16, [1, 77, 5120]> input_159_cast = 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, x = input_157_cast)[name = tensor<string, []>("input_159_cast")]; |
| 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 = gelu(mode = input_161_mode_0, x = input_159_cast)[name = tensor<string, []>("input_161_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(507142912)))]; |
| 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, []>(520250176)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_59_cast = 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, x = input_161_cast)[name = tensor<string, []>("hidden_states_59_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_163_cast = add(x = input_155_cast, y = hidden_states_59_cast)[name = tensor<string, []>("input_163_cast")]; |
| 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, []>(520252800)))]; |
| 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, []>(520255424)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_61_cast = 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)[name = tensor<string, []>("hidden_states_61_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(520258048)))]; |
| 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, []>(523534912)))]; |
| tensor<fp16, [1, 77, 1280]> var_1018_cast = 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, x = hidden_states_61_cast)[name = tensor<string, []>("op_1018_cast")]; |
| tensor<fp16, []> var_1019_to_fp16 = const()[name = tensor<string, []>("op_1019_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_65_cast = mul(x = var_1018_cast, y = var_1019_to_fp16)[name = tensor<string, []>("tensor_65_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(523537536)))]; |
| 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, []>(526814400)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_61_cast = 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, x = hidden_states_61_cast)[name = tensor<string, []>("tensor_61_cast")]; |
| tensor<int32, [4]> var_1024 = const()[name = tensor<string, []>("op_1024"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1025_cast = reshape(shape = var_1024, x = tensor_61_cast)[name = tensor<string, []>("op_1025_cast")]; |
| tensor<int32, [4]> var_1026_perm_0 = const()[name = tensor<string, []>("op_1026_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(526817024)))]; |
| 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, []>(530093888)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_63_cast = 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, x = hidden_states_61_cast)[name = tensor<string, []>("tensor_63_cast")]; |
| tensor<int32, [4]> var_1031 = const()[name = tensor<string, []>("op_1031"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1032_cast = reshape(shape = var_1031, x = tensor_63_cast)[name = tensor<string, []>("op_1032_cast")]; |
| tensor<int32, [4]> var_1033_perm_0 = const()[name = tensor<string, []>("op_1033_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_1040 = const()[name = tensor<string, []>("op_1040"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1041_cast = reshape(shape = var_1040, x = tensor_65_cast)[name = tensor<string, []>("op_1041_cast")]; |
| tensor<int32, [4]> var_1042_perm_0 = const()[name = tensor<string, []>("op_1042_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_1044 = const()[name = tensor<string, []>("op_1044"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_108 = transpose(perm = var_1042_perm_0, x = var_1041_cast)[name = tensor<string, []>("transpose_108")]; |
| tensor<fp16, [20, 77, 64]> query_states_21_cast = reshape(shape = var_1044, x = transpose_108)[name = tensor<string, []>("query_states_21_cast")]; |
| tensor<int32, [3]> var_1046 = const()[name = tensor<string, []>("op_1046"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_110 = transpose(perm = var_1026_perm_0, x = var_1025_cast)[name = tensor<string, []>("transpose_110")]; |
| tensor<fp16, [20, 77, 64]> key_states_43_cast = reshape(shape = var_1046, x = transpose_110)[name = tensor<string, []>("key_states_43_cast")]; |
| tensor<int32, [3]> var_1048 = const()[name = tensor<string, []>("op_1048"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_109 = transpose(perm = var_1033_perm_0, x = var_1032_cast)[name = tensor<string, []>("transpose_109")]; |
| tensor<fp16, [20, 77, 64]> value_states_43_cast = reshape(shape = var_1048, x = transpose_109)[name = tensor<string, []>("value_states_43_cast")]; |
| tensor<int32, [3]> var_1051_perm_0 = const()[name = tensor<string, []>("op_1051_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_61_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_61_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_61_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_61_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_107 = transpose(perm = var_1051_perm_0, x = key_states_43_cast)[name = tensor<string, []>("transpose_107")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_61_cast = matmul(transpose_x = attn_weights_61_transpose_x_0, transpose_y = attn_weights_61_transpose_y_0, x = query_states_21_cast, y = transpose_107)[name = tensor<string, []>("attn_weights_61_cast")]; |
| tensor<int32, [4]> var_1053 = const()[name = tensor<string, []>("op_1053"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_1054_cast = reshape(shape = var_1053, x = attn_weights_61_cast)[name = tensor<string, []>("op_1054_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_63_cast = add(x = var_1054_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_63_cast")]; |
| tensor<int32, [3]> var_1059 = const()[name = tensor<string, []>("op_1059"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_165_cast = reshape(shape = var_1059, x = attn_weights_63_cast)[name = tensor<string, []>("input_165_cast")]; |
| tensor<fp16, [20, 77, 77]> input_167_cast = softmax(axis = var_5, x = input_165_cast)[name = tensor<string, []>("input_167_cast")]; |
| 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 = matmul(transpose_x = attn_output_61_transpose_x_0, transpose_y = attn_output_61_transpose_y_0, x = input_167_cast, y = value_states_43_cast)[name = tensor<string, []>("attn_output_61_cast")]; |
| tensor<int32, [4]> var_1064 = const()[name = tensor<string, []>("op_1064"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_63_cast = reshape(shape = var_1064, x = attn_output_61_cast)[name = tensor<string, []>("attn_output_63_cast")]; |
| 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_1067 = const()[name = tensor<string, []>("op_1067"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_106 = transpose(perm = attn_output_65_perm_0, x = attn_output_63_cast)[name = tensor<string, []>("transpose_106")]; |
| tensor<fp16, [1, 77, 1280]> input_169_cast = reshape(shape = var_1067, x = transpose_106)[name = tensor<string, []>("input_169_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(530096512)))]; |
| 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, []>(533373376)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_63_cast = 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, x = input_169_cast)[name = tensor<string, []>("hidden_states_63_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_171_cast = add(x = input_163_cast, y = hidden_states_63_cast)[name = tensor<string, []>("input_171_cast")]; |
| 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, []>(533376000)))]; |
| 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, []>(533378624)))]; |
| tensor<fp16, [1, 77, 1280]> input_173_cast = 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)[name = tensor<string, []>("input_173_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(533381248)))]; |
| 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, []>(546488512)))]; |
| tensor<fp16, [1, 77, 5120]> input_175_cast = 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, x = input_173_cast)[name = tensor<string, []>("input_175_cast")]; |
| 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 = gelu(mode = input_177_mode_0, x = input_175_cast)[name = tensor<string, []>("input_177_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(546498816)))]; |
| 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, []>(559606080)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_65_cast = 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, x = input_177_cast)[name = tensor<string, []>("hidden_states_65_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_179_cast = add(x = input_171_cast, y = hidden_states_65_cast)[name = tensor<string, []>("input_179_cast")]; |
| 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, []>(559608704)))]; |
| 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, []>(559611328)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_67_cast = 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)[name = tensor<string, []>("hidden_states_67_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(559613952)))]; |
| 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, []>(562890816)))]; |
| tensor<fp16, [1, 77, 1280]> var_1105_cast = 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, x = hidden_states_67_cast)[name = tensor<string, []>("op_1105_cast")]; |
| tensor<fp16, []> var_1106_to_fp16 = const()[name = tensor<string, []>("op_1106_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_71_cast = mul(x = var_1105_cast, y = var_1106_to_fp16)[name = tensor<string, []>("tensor_71_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(562893440)))]; |
| 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, []>(566170304)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_67_cast = 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, x = hidden_states_67_cast)[name = tensor<string, []>("tensor_67_cast")]; |
| tensor<int32, [4]> var_1111 = const()[name = tensor<string, []>("op_1111"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1112_cast = reshape(shape = var_1111, x = tensor_67_cast)[name = tensor<string, []>("op_1112_cast")]; |
| tensor<int32, [4]> var_1113_perm_0 = const()[name = tensor<string, []>("op_1113_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(566172928)))]; |
| 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, []>(569449792)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_69_cast = 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, x = hidden_states_67_cast)[name = tensor<string, []>("tensor_69_cast")]; |
| tensor<int32, [4]> var_1118 = const()[name = tensor<string, []>("op_1118"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1119_cast = reshape(shape = var_1118, x = tensor_69_cast)[name = tensor<string, []>("op_1119_cast")]; |
| tensor<int32, [4]> var_1120_perm_0 = const()[name = tensor<string, []>("op_1120_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_1127 = const()[name = tensor<string, []>("op_1127"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1128_cast = reshape(shape = var_1127, x = tensor_71_cast)[name = tensor<string, []>("op_1128_cast")]; |
| tensor<int32, [4]> var_1129_perm_0 = const()[name = tensor<string, []>("op_1129_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_1131 = const()[name = tensor<string, []>("op_1131"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_103 = transpose(perm = var_1129_perm_0, x = var_1128_cast)[name = tensor<string, []>("transpose_103")]; |
| tensor<fp16, [20, 77, 64]> query_states_23_cast = reshape(shape = var_1131, x = transpose_103)[name = tensor<string, []>("query_states_23_cast")]; |
| tensor<int32, [3]> var_1133 = const()[name = tensor<string, []>("op_1133"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_105 = transpose(perm = var_1113_perm_0, x = var_1112_cast)[name = tensor<string, []>("transpose_105")]; |
| tensor<fp16, [20, 77, 64]> key_states_47_cast = reshape(shape = var_1133, x = transpose_105)[name = tensor<string, []>("key_states_47_cast")]; |
| tensor<int32, [3]> var_1135 = const()[name = tensor<string, []>("op_1135"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_104 = transpose(perm = var_1120_perm_0, x = var_1119_cast)[name = tensor<string, []>("transpose_104")]; |
| tensor<fp16, [20, 77, 64]> value_states_47_cast = reshape(shape = var_1135, x = transpose_104)[name = tensor<string, []>("value_states_47_cast")]; |
| tensor<int32, [3]> var_1138_perm_0 = const()[name = tensor<string, []>("op_1138_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_67_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_67_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_67_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_67_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_102 = transpose(perm = var_1138_perm_0, x = key_states_47_cast)[name = tensor<string, []>("transpose_102")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_67_cast = matmul(transpose_x = attn_weights_67_transpose_x_0, transpose_y = attn_weights_67_transpose_y_0, x = query_states_23_cast, y = transpose_102)[name = tensor<string, []>("attn_weights_67_cast")]; |
| tensor<int32, [4]> var_1140 = const()[name = tensor<string, []>("op_1140"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_1141_cast = reshape(shape = var_1140, x = attn_weights_67_cast)[name = tensor<string, []>("op_1141_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_69_cast = add(x = var_1141_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_69_cast")]; |
| tensor<int32, [3]> var_1146 = const()[name = tensor<string, []>("op_1146"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_181_cast = reshape(shape = var_1146, x = attn_weights_69_cast)[name = tensor<string, []>("input_181_cast")]; |
| tensor<fp16, [20, 77, 77]> input_183_cast = softmax(axis = var_5, x = input_181_cast)[name = tensor<string, []>("input_183_cast")]; |
| 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 = matmul(transpose_x = attn_output_67_transpose_x_0, transpose_y = attn_output_67_transpose_y_0, x = input_183_cast, y = value_states_47_cast)[name = tensor<string, []>("attn_output_67_cast")]; |
| tensor<int32, [4]> var_1151 = const()[name = tensor<string, []>("op_1151"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_69_cast = reshape(shape = var_1151, x = attn_output_67_cast)[name = tensor<string, []>("attn_output_69_cast")]; |
| 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_1154 = const()[name = tensor<string, []>("op_1154"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_101 = transpose(perm = attn_output_71_perm_0, x = attn_output_69_cast)[name = tensor<string, []>("transpose_101")]; |
| tensor<fp16, [1, 77, 1280]> input_185_cast = reshape(shape = var_1154, x = transpose_101)[name = tensor<string, []>("input_185_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(569452416)))]; |
| 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, []>(572729280)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_69_cast = 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, x = input_185_cast)[name = tensor<string, []>("hidden_states_69_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_187_cast = add(x = input_179_cast, y = hidden_states_69_cast)[name = tensor<string, []>("input_187_cast")]; |
| 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, []>(572731904)))]; |
| 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, []>(572734528)))]; |
| tensor<fp16, [1, 77, 1280]> input_189_cast = 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)[name = tensor<string, []>("input_189_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(572737152)))]; |
| 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, []>(585844416)))]; |
| tensor<fp16, [1, 77, 5120]> input_191_cast = 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, x = input_189_cast)[name = tensor<string, []>("input_191_cast")]; |
| 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 = gelu(mode = input_193_mode_0, x = input_191_cast)[name = tensor<string, []>("input_193_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(585854720)))]; |
| 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, []>(598961984)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_71_cast = 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, x = input_193_cast)[name = tensor<string, []>("hidden_states_71_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_195_cast = add(x = input_187_cast, y = hidden_states_71_cast)[name = tensor<string, []>("input_195_cast")]; |
| 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, []>(598964608)))]; |
| 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, []>(598967232)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_73_cast = 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)[name = tensor<string, []>("hidden_states_73_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(598969856)))]; |
| 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, []>(602246720)))]; |
| tensor<fp16, [1, 77, 1280]> var_1192_cast = 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, x = hidden_states_73_cast)[name = tensor<string, []>("op_1192_cast")]; |
| tensor<fp16, []> var_1193_to_fp16 = const()[name = tensor<string, []>("op_1193_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_77_cast = mul(x = var_1192_cast, y = var_1193_to_fp16)[name = tensor<string, []>("tensor_77_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(602249344)))]; |
| 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, []>(605526208)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_73_cast = 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, x = hidden_states_73_cast)[name = tensor<string, []>("tensor_73_cast")]; |
| tensor<int32, [4]> var_1198 = const()[name = tensor<string, []>("op_1198"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1199_cast = reshape(shape = var_1198, x = tensor_73_cast)[name = tensor<string, []>("op_1199_cast")]; |
| tensor<int32, [4]> var_1200_perm_0 = const()[name = tensor<string, []>("op_1200_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(605528832)))]; |
| 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, []>(608805696)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_75_cast = 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, x = hidden_states_73_cast)[name = tensor<string, []>("tensor_75_cast")]; |
| tensor<int32, [4]> var_1205 = const()[name = tensor<string, []>("op_1205"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1206_cast = reshape(shape = var_1205, x = tensor_75_cast)[name = tensor<string, []>("op_1206_cast")]; |
| tensor<int32, [4]> var_1207_perm_0 = const()[name = tensor<string, []>("op_1207_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_1214 = const()[name = tensor<string, []>("op_1214"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1215_cast = reshape(shape = var_1214, x = tensor_77_cast)[name = tensor<string, []>("op_1215_cast")]; |
| tensor<int32, [4]> var_1216_perm_0 = const()[name = tensor<string, []>("op_1216_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_1218 = const()[name = tensor<string, []>("op_1218"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_98 = transpose(perm = var_1216_perm_0, x = var_1215_cast)[name = tensor<string, []>("transpose_98")]; |
| tensor<fp16, [20, 77, 64]> query_states_25_cast = reshape(shape = var_1218, x = transpose_98)[name = tensor<string, []>("query_states_25_cast")]; |
| tensor<int32, [3]> var_1220 = const()[name = tensor<string, []>("op_1220"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_100 = transpose(perm = var_1200_perm_0, x = var_1199_cast)[name = tensor<string, []>("transpose_100")]; |
| tensor<fp16, [20, 77, 64]> key_states_51_cast = reshape(shape = var_1220, x = transpose_100)[name = tensor<string, []>("key_states_51_cast")]; |
| tensor<int32, [3]> var_1222 = const()[name = tensor<string, []>("op_1222"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_99 = transpose(perm = var_1207_perm_0, x = var_1206_cast)[name = tensor<string, []>("transpose_99")]; |
| tensor<fp16, [20, 77, 64]> value_states_51_cast = reshape(shape = var_1222, x = transpose_99)[name = tensor<string, []>("value_states_51_cast")]; |
| tensor<int32, [3]> var_1225_perm_0 = const()[name = tensor<string, []>("op_1225_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_73_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_73_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_73_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_73_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_97 = transpose(perm = var_1225_perm_0, x = key_states_51_cast)[name = tensor<string, []>("transpose_97")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_73_cast = matmul(transpose_x = attn_weights_73_transpose_x_0, transpose_y = attn_weights_73_transpose_y_0, x = query_states_25_cast, y = transpose_97)[name = tensor<string, []>("attn_weights_73_cast")]; |
| tensor<int32, [4]> var_1227 = const()[name = tensor<string, []>("op_1227"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_1228_cast = reshape(shape = var_1227, x = attn_weights_73_cast)[name = tensor<string, []>("op_1228_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_75_cast = add(x = var_1228_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_75_cast")]; |
| tensor<int32, [3]> var_1233 = const()[name = tensor<string, []>("op_1233"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_197_cast = reshape(shape = var_1233, x = attn_weights_75_cast)[name = tensor<string, []>("input_197_cast")]; |
| tensor<fp16, [20, 77, 77]> input_199_cast = softmax(axis = var_5, x = input_197_cast)[name = tensor<string, []>("input_199_cast")]; |
| 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 = matmul(transpose_x = attn_output_73_transpose_x_0, transpose_y = attn_output_73_transpose_y_0, x = input_199_cast, y = value_states_51_cast)[name = tensor<string, []>("attn_output_73_cast")]; |
| tensor<int32, [4]> var_1238 = const()[name = tensor<string, []>("op_1238"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_75_cast = reshape(shape = var_1238, x = attn_output_73_cast)[name = tensor<string, []>("attn_output_75_cast")]; |
| 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_1241 = const()[name = tensor<string, []>("op_1241"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_96 = transpose(perm = attn_output_77_perm_0, x = attn_output_75_cast)[name = tensor<string, []>("transpose_96")]; |
| tensor<fp16, [1, 77, 1280]> input_201_cast = reshape(shape = var_1241, x = transpose_96)[name = tensor<string, []>("input_201_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(608808320)))]; |
| 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, []>(612085184)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_75_cast = 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, x = input_201_cast)[name = tensor<string, []>("hidden_states_75_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_203_cast = add(x = input_195_cast, y = hidden_states_75_cast)[name = tensor<string, []>("input_203_cast")]; |
| 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, []>(612087808)))]; |
| 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, []>(612090432)))]; |
| tensor<fp16, [1, 77, 1280]> input_205_cast = 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)[name = tensor<string, []>("input_205_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(612093056)))]; |
| 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, []>(625200320)))]; |
| tensor<fp16, [1, 77, 5120]> input_207_cast = 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, x = input_205_cast)[name = tensor<string, []>("input_207_cast")]; |
| 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 = gelu(mode = input_209_mode_0, x = input_207_cast)[name = tensor<string, []>("input_209_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_12_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(625210624)))]; |
| 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, []>(638317888)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_77_cast = 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, x = input_209_cast)[name = tensor<string, []>("hidden_states_77_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_211_cast = add(x = input_203_cast, y = hidden_states_77_cast)[name = tensor<string, []>("input_211_cast")]; |
| 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, []>(638320512)))]; |
| 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, []>(638323136)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_79_cast = 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)[name = tensor<string, []>("hidden_states_79_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(638325760)))]; |
| 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, []>(641602624)))]; |
| tensor<fp16, [1, 77, 1280]> var_1279_cast = 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, x = hidden_states_79_cast)[name = tensor<string, []>("op_1279_cast")]; |
| tensor<fp16, []> var_1280_to_fp16 = const()[name = tensor<string, []>("op_1280_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_83_cast = mul(x = var_1279_cast, y = var_1280_to_fp16)[name = tensor<string, []>("tensor_83_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(641605248)))]; |
| 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, []>(644882112)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_79_cast = 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, x = hidden_states_79_cast)[name = tensor<string, []>("tensor_79_cast")]; |
| tensor<int32, [4]> var_1285 = const()[name = tensor<string, []>("op_1285"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1286_cast = reshape(shape = var_1285, x = tensor_79_cast)[name = tensor<string, []>("op_1286_cast")]; |
| tensor<int32, [4]> var_1287_perm_0 = const()[name = tensor<string, []>("op_1287_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(644884736)))]; |
| 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, []>(648161600)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_81_cast = 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, x = hidden_states_79_cast)[name = tensor<string, []>("tensor_81_cast")]; |
| tensor<int32, [4]> var_1292 = const()[name = tensor<string, []>("op_1292"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1293_cast = reshape(shape = var_1292, x = tensor_81_cast)[name = tensor<string, []>("op_1293_cast")]; |
| tensor<int32, [4]> var_1294_perm_0 = const()[name = tensor<string, []>("op_1294_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_1301 = const()[name = tensor<string, []>("op_1301"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1302_cast = reshape(shape = var_1301, x = tensor_83_cast)[name = tensor<string, []>("op_1302_cast")]; |
| tensor<int32, [4]> var_1303_perm_0 = const()[name = tensor<string, []>("op_1303_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_1305 = const()[name = tensor<string, []>("op_1305"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_93 = transpose(perm = var_1303_perm_0, x = var_1302_cast)[name = tensor<string, []>("transpose_93")]; |
| tensor<fp16, [20, 77, 64]> query_states_27_cast = reshape(shape = var_1305, x = transpose_93)[name = tensor<string, []>("query_states_27_cast")]; |
| tensor<int32, [3]> var_1307 = const()[name = tensor<string, []>("op_1307"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_95 = transpose(perm = var_1287_perm_0, x = var_1286_cast)[name = tensor<string, []>("transpose_95")]; |
| tensor<fp16, [20, 77, 64]> key_states_55_cast = reshape(shape = var_1307, x = transpose_95)[name = tensor<string, []>("key_states_55_cast")]; |
| tensor<int32, [3]> var_1309 = const()[name = tensor<string, []>("op_1309"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_94 = transpose(perm = var_1294_perm_0, x = var_1293_cast)[name = tensor<string, []>("transpose_94")]; |
| tensor<fp16, [20, 77, 64]> value_states_55_cast = reshape(shape = var_1309, x = transpose_94)[name = tensor<string, []>("value_states_55_cast")]; |
| tensor<int32, [3]> var_1312_perm_0 = const()[name = tensor<string, []>("op_1312_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_79_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_79_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_79_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_79_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_92 = transpose(perm = var_1312_perm_0, x = key_states_55_cast)[name = tensor<string, []>("transpose_92")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_79_cast = matmul(transpose_x = attn_weights_79_transpose_x_0, transpose_y = attn_weights_79_transpose_y_0, x = query_states_27_cast, y = transpose_92)[name = tensor<string, []>("attn_weights_79_cast")]; |
| tensor<int32, [4]> var_1314 = const()[name = tensor<string, []>("op_1314"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_1315_cast = reshape(shape = var_1314, x = attn_weights_79_cast)[name = tensor<string, []>("op_1315_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_81_cast = add(x = var_1315_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_81_cast")]; |
| tensor<int32, [3]> var_1320 = const()[name = tensor<string, []>("op_1320"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_213_cast = reshape(shape = var_1320, x = attn_weights_81_cast)[name = tensor<string, []>("input_213_cast")]; |
| tensor<fp16, [20, 77, 77]> input_215_cast = softmax(axis = var_5, x = input_213_cast)[name = tensor<string, []>("input_215_cast")]; |
| 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 = matmul(transpose_x = attn_output_79_transpose_x_0, transpose_y = attn_output_79_transpose_y_0, x = input_215_cast, y = value_states_55_cast)[name = tensor<string, []>("attn_output_79_cast")]; |
| tensor<int32, [4]> var_1325 = const()[name = tensor<string, []>("op_1325"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_81_cast = reshape(shape = var_1325, x = attn_output_79_cast)[name = tensor<string, []>("attn_output_81_cast")]; |
| 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_1328 = const()[name = tensor<string, []>("op_1328"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_91 = transpose(perm = attn_output_83_perm_0, x = attn_output_81_cast)[name = tensor<string, []>("transpose_91")]; |
| tensor<fp16, [1, 77, 1280]> input_217_cast = reshape(shape = var_1328, x = transpose_91)[name = tensor<string, []>("input_217_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(648164224)))]; |
| 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, []>(651441088)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_81_cast = 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, x = input_217_cast)[name = tensor<string, []>("hidden_states_81_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_219_cast = add(x = input_211_cast, y = hidden_states_81_cast)[name = tensor<string, []>("input_219_cast")]; |
| 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, []>(651443712)))]; |
| 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, []>(651446336)))]; |
| tensor<fp16, [1, 77, 1280]> input_221_cast = 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)[name = tensor<string, []>("input_221_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(651448960)))]; |
| 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, []>(664556224)))]; |
| tensor<fp16, [1, 77, 5120]> input_223_cast = 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, x = input_221_cast)[name = tensor<string, []>("input_223_cast")]; |
| 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 = gelu(mode = input_225_mode_0, x = input_223_cast)[name = tensor<string, []>("input_225_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_13_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(664566528)))]; |
| 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, []>(677673792)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_83_cast = 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, x = input_225_cast)[name = tensor<string, []>("hidden_states_83_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_227_cast = add(x = input_219_cast, y = hidden_states_83_cast)[name = tensor<string, []>("input_227_cast")]; |
| 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, []>(677676416)))]; |
| 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, []>(677679040)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_85_cast = 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)[name = tensor<string, []>("hidden_states_85_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(677681664)))]; |
| 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, []>(680958528)))]; |
| tensor<fp16, [1, 77, 1280]> var_1366_cast = 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, x = hidden_states_85_cast)[name = tensor<string, []>("op_1366_cast")]; |
| tensor<fp16, []> var_1367_to_fp16 = const()[name = tensor<string, []>("op_1367_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_89_cast = mul(x = var_1366_cast, y = var_1367_to_fp16)[name = tensor<string, []>("tensor_89_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(680961152)))]; |
| 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, []>(684238016)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_85_cast = 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, x = hidden_states_85_cast)[name = tensor<string, []>("tensor_85_cast")]; |
| tensor<int32, [4]> var_1372 = const()[name = tensor<string, []>("op_1372"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1373_cast = reshape(shape = var_1372, x = tensor_85_cast)[name = tensor<string, []>("op_1373_cast")]; |
| tensor<int32, [4]> var_1374_perm_0 = const()[name = tensor<string, []>("op_1374_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(684240640)))]; |
| 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, []>(687517504)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_87_cast = 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, x = hidden_states_85_cast)[name = tensor<string, []>("tensor_87_cast")]; |
| tensor<int32, [4]> var_1379 = const()[name = tensor<string, []>("op_1379"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1380_cast = reshape(shape = var_1379, x = tensor_87_cast)[name = tensor<string, []>("op_1380_cast")]; |
| tensor<int32, [4]> var_1381_perm_0 = const()[name = tensor<string, []>("op_1381_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_1388 = const()[name = tensor<string, []>("op_1388"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1389_cast = reshape(shape = var_1388, x = tensor_89_cast)[name = tensor<string, []>("op_1389_cast")]; |
| tensor<int32, [4]> var_1390_perm_0 = const()[name = tensor<string, []>("op_1390_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_1392 = const()[name = tensor<string, []>("op_1392"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_88 = transpose(perm = var_1390_perm_0, x = var_1389_cast)[name = tensor<string, []>("transpose_88")]; |
| tensor<fp16, [20, 77, 64]> query_states_29_cast = reshape(shape = var_1392, x = transpose_88)[name = tensor<string, []>("query_states_29_cast")]; |
| tensor<int32, [3]> var_1394 = const()[name = tensor<string, []>("op_1394"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_90 = transpose(perm = var_1374_perm_0, x = var_1373_cast)[name = tensor<string, []>("transpose_90")]; |
| tensor<fp16, [20, 77, 64]> key_states_59_cast = reshape(shape = var_1394, x = transpose_90)[name = tensor<string, []>("key_states_59_cast")]; |
| tensor<int32, [3]> var_1396 = const()[name = tensor<string, []>("op_1396"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_89 = transpose(perm = var_1381_perm_0, x = var_1380_cast)[name = tensor<string, []>("transpose_89")]; |
| tensor<fp16, [20, 77, 64]> value_states_59_cast = reshape(shape = var_1396, x = transpose_89)[name = tensor<string, []>("value_states_59_cast")]; |
| tensor<int32, [3]> var_1399_perm_0 = const()[name = tensor<string, []>("op_1399_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_85_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_85_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_85_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_85_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_87 = transpose(perm = var_1399_perm_0, x = key_states_59_cast)[name = tensor<string, []>("transpose_87")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_85_cast = matmul(transpose_x = attn_weights_85_transpose_x_0, transpose_y = attn_weights_85_transpose_y_0, x = query_states_29_cast, y = transpose_87)[name = tensor<string, []>("attn_weights_85_cast")]; |
| tensor<int32, [4]> var_1401 = const()[name = tensor<string, []>("op_1401"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_1402_cast = reshape(shape = var_1401, x = attn_weights_85_cast)[name = tensor<string, []>("op_1402_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_87_cast = add(x = var_1402_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_87_cast")]; |
| tensor<int32, [3]> var_1407 = const()[name = tensor<string, []>("op_1407"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_229_cast = reshape(shape = var_1407, x = attn_weights_87_cast)[name = tensor<string, []>("input_229_cast")]; |
| tensor<fp16, [20, 77, 77]> input_231_cast = softmax(axis = var_5, x = input_229_cast)[name = tensor<string, []>("input_231_cast")]; |
| 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 = matmul(transpose_x = attn_output_85_transpose_x_0, transpose_y = attn_output_85_transpose_y_0, x = input_231_cast, y = value_states_59_cast)[name = tensor<string, []>("attn_output_85_cast")]; |
| tensor<int32, [4]> var_1412 = const()[name = tensor<string, []>("op_1412"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_87_cast = reshape(shape = var_1412, x = attn_output_85_cast)[name = tensor<string, []>("attn_output_87_cast")]; |
| 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_1415 = const()[name = tensor<string, []>("op_1415"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_86 = transpose(perm = attn_output_89_perm_0, x = attn_output_87_cast)[name = tensor<string, []>("transpose_86")]; |
| tensor<fp16, [1, 77, 1280]> input_233_cast = reshape(shape = var_1415, x = transpose_86)[name = tensor<string, []>("input_233_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(687520128)))]; |
| 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, []>(690796992)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_87_cast = 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, x = input_233_cast)[name = tensor<string, []>("hidden_states_87_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_235_cast = add(x = input_227_cast, y = hidden_states_87_cast)[name = tensor<string, []>("input_235_cast")]; |
| 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, []>(690799616)))]; |
| 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, []>(690802240)))]; |
| tensor<fp16, [1, 77, 1280]> input_237_cast = 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)[name = tensor<string, []>("input_237_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(690804864)))]; |
| 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, []>(703912128)))]; |
| tensor<fp16, [1, 77, 5120]> input_239_cast = 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, x = input_237_cast)[name = tensor<string, []>("input_239_cast")]; |
| 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 = gelu(mode = input_241_mode_0, x = input_239_cast)[name = tensor<string, []>("input_241_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_14_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(703922432)))]; |
| 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, []>(717029696)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_89_cast = 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, x = input_241_cast)[name = tensor<string, []>("hidden_states_89_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_243_cast = add(x = input_235_cast, y = hidden_states_89_cast)[name = tensor<string, []>("input_243_cast")]; |
| 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, []>(717032320)))]; |
| 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, []>(717034944)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_91_cast = 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)[name = tensor<string, []>("hidden_states_91_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(717037568)))]; |
| 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, []>(720314432)))]; |
| tensor<fp16, [1, 77, 1280]> var_1453_cast = 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, x = hidden_states_91_cast)[name = tensor<string, []>("op_1453_cast")]; |
| tensor<fp16, []> var_1454_to_fp16 = const()[name = tensor<string, []>("op_1454_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_95_cast = mul(x = var_1453_cast, y = var_1454_to_fp16)[name = tensor<string, []>("tensor_95_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(720317056)))]; |
| 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, []>(723593920)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_91_cast = 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, x = hidden_states_91_cast)[name = tensor<string, []>("tensor_91_cast")]; |
| tensor<int32, [4]> var_1459 = const()[name = tensor<string, []>("op_1459"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1460_cast = reshape(shape = var_1459, x = tensor_91_cast)[name = tensor<string, []>("op_1460_cast")]; |
| tensor<int32, [4]> var_1461_perm_0 = const()[name = tensor<string, []>("op_1461_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(723596544)))]; |
| 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, []>(726873408)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_93_cast = 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, x = hidden_states_91_cast)[name = tensor<string, []>("tensor_93_cast")]; |
| tensor<int32, [4]> var_1466 = const()[name = tensor<string, []>("op_1466"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1467_cast = reshape(shape = var_1466, x = tensor_93_cast)[name = tensor<string, []>("op_1467_cast")]; |
| tensor<int32, [4]> var_1468_perm_0 = const()[name = tensor<string, []>("op_1468_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_1475 = const()[name = tensor<string, []>("op_1475"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1476_cast = reshape(shape = var_1475, x = tensor_95_cast)[name = tensor<string, []>("op_1476_cast")]; |
| tensor<int32, [4]> var_1477_perm_0 = const()[name = tensor<string, []>("op_1477_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_1479 = const()[name = tensor<string, []>("op_1479"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_83 = transpose(perm = var_1477_perm_0, x = var_1476_cast)[name = tensor<string, []>("transpose_83")]; |
| tensor<fp16, [20, 77, 64]> query_states_31_cast = reshape(shape = var_1479, x = transpose_83)[name = tensor<string, []>("query_states_31_cast")]; |
| tensor<int32, [3]> var_1481 = const()[name = tensor<string, []>("op_1481"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_85 = transpose(perm = var_1461_perm_0, x = var_1460_cast)[name = tensor<string, []>("transpose_85")]; |
| tensor<fp16, [20, 77, 64]> key_states_63_cast = reshape(shape = var_1481, x = transpose_85)[name = tensor<string, []>("key_states_63_cast")]; |
| tensor<int32, [3]> var_1483 = const()[name = tensor<string, []>("op_1483"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_84 = transpose(perm = var_1468_perm_0, x = var_1467_cast)[name = tensor<string, []>("transpose_84")]; |
| tensor<fp16, [20, 77, 64]> value_states_63_cast = reshape(shape = var_1483, x = transpose_84)[name = tensor<string, []>("value_states_63_cast")]; |
| tensor<int32, [3]> var_1486_perm_0 = const()[name = tensor<string, []>("op_1486_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_91_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_91_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_91_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_91_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_82 = transpose(perm = var_1486_perm_0, x = key_states_63_cast)[name = tensor<string, []>("transpose_82")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_91_cast = matmul(transpose_x = attn_weights_91_transpose_x_0, transpose_y = attn_weights_91_transpose_y_0, x = query_states_31_cast, y = transpose_82)[name = tensor<string, []>("attn_weights_91_cast")]; |
| tensor<int32, [4]> var_1488 = const()[name = tensor<string, []>("op_1488"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_1489_cast = reshape(shape = var_1488, x = attn_weights_91_cast)[name = tensor<string, []>("op_1489_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_93_cast = add(x = var_1489_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_93_cast")]; |
| tensor<int32, [3]> var_1494 = const()[name = tensor<string, []>("op_1494"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_245_cast = reshape(shape = var_1494, x = attn_weights_93_cast)[name = tensor<string, []>("input_245_cast")]; |
| tensor<fp16, [20, 77, 77]> input_247_cast = softmax(axis = var_5, x = input_245_cast)[name = tensor<string, []>("input_247_cast")]; |
| 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 = matmul(transpose_x = attn_output_91_transpose_x_0, transpose_y = attn_output_91_transpose_y_0, x = input_247_cast, y = value_states_63_cast)[name = tensor<string, []>("attn_output_91_cast")]; |
| tensor<int32, [4]> var_1499 = const()[name = tensor<string, []>("op_1499"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_93_cast = reshape(shape = var_1499, x = attn_output_91_cast)[name = tensor<string, []>("attn_output_93_cast")]; |
| 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_1502 = const()[name = tensor<string, []>("op_1502"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_81 = transpose(perm = attn_output_95_perm_0, x = attn_output_93_cast)[name = tensor<string, []>("transpose_81")]; |
| tensor<fp16, [1, 77, 1280]> input_249_cast = reshape(shape = var_1502, x = transpose_81)[name = tensor<string, []>("input_249_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(726876032)))]; |
| 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, []>(730152896)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_93_cast = 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, x = input_249_cast)[name = tensor<string, []>("hidden_states_93_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_251_cast = add(x = input_243_cast, y = hidden_states_93_cast)[name = tensor<string, []>("input_251_cast")]; |
| 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, []>(730155520)))]; |
| 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, []>(730158144)))]; |
| tensor<fp16, [1, 77, 1280]> input_253_cast = 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)[name = tensor<string, []>("input_253_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(730160768)))]; |
| 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, []>(743268032)))]; |
| tensor<fp16, [1, 77, 5120]> input_255_cast = 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, x = input_253_cast)[name = tensor<string, []>("input_255_cast")]; |
| 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 = gelu(mode = input_257_mode_0, x = input_255_cast)[name = tensor<string, []>("input_257_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_15_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(743278336)))]; |
| 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, []>(756385600)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_95_cast = 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, x = input_257_cast)[name = tensor<string, []>("hidden_states_95_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_259_cast = add(x = input_251_cast, y = hidden_states_95_cast)[name = tensor<string, []>("input_259_cast")]; |
| 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, []>(756388224)))]; |
| 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, []>(756390848)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_97_cast = 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)[name = tensor<string, []>("hidden_states_97_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(756393472)))]; |
| 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, []>(759670336)))]; |
| tensor<fp16, [1, 77, 1280]> var_1540_cast = 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, x = hidden_states_97_cast)[name = tensor<string, []>("op_1540_cast")]; |
| tensor<fp16, []> var_1541_to_fp16 = const()[name = tensor<string, []>("op_1541_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_101_cast = mul(x = var_1540_cast, y = var_1541_to_fp16)[name = tensor<string, []>("tensor_101_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(759672960)))]; |
| 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, []>(762949824)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_97_cast = 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, x = hidden_states_97_cast)[name = tensor<string, []>("tensor_97_cast")]; |
| tensor<int32, [4]> var_1546 = const()[name = tensor<string, []>("op_1546"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1547_cast = reshape(shape = var_1546, x = tensor_97_cast)[name = tensor<string, []>("op_1547_cast")]; |
| tensor<int32, [4]> var_1548_perm_0 = const()[name = tensor<string, []>("op_1548_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(762952448)))]; |
| 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, []>(766229312)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_99_cast = 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, x = hidden_states_97_cast)[name = tensor<string, []>("tensor_99_cast")]; |
| tensor<int32, [4]> var_1553 = const()[name = tensor<string, []>("op_1553"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1554_cast = reshape(shape = var_1553, x = tensor_99_cast)[name = tensor<string, []>("op_1554_cast")]; |
| tensor<int32, [4]> var_1555_perm_0 = const()[name = tensor<string, []>("op_1555_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_1562 = const()[name = tensor<string, []>("op_1562"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1563_cast = reshape(shape = var_1562, x = tensor_101_cast)[name = tensor<string, []>("op_1563_cast")]; |
| tensor<int32, [4]> var_1564_perm_0 = const()[name = tensor<string, []>("op_1564_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_1566 = const()[name = tensor<string, []>("op_1566"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_78 = transpose(perm = var_1564_perm_0, x = var_1563_cast)[name = tensor<string, []>("transpose_78")]; |
| tensor<fp16, [20, 77, 64]> query_states_33_cast = reshape(shape = var_1566, x = transpose_78)[name = tensor<string, []>("query_states_33_cast")]; |
| tensor<int32, [3]> var_1568 = const()[name = tensor<string, []>("op_1568"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_80 = transpose(perm = var_1548_perm_0, x = var_1547_cast)[name = tensor<string, []>("transpose_80")]; |
| tensor<fp16, [20, 77, 64]> key_states_67_cast = reshape(shape = var_1568, x = transpose_80)[name = tensor<string, []>("key_states_67_cast")]; |
| tensor<int32, [3]> var_1570 = const()[name = tensor<string, []>("op_1570"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_79 = transpose(perm = var_1555_perm_0, x = var_1554_cast)[name = tensor<string, []>("transpose_79")]; |
| tensor<fp16, [20, 77, 64]> value_states_67_cast = reshape(shape = var_1570, x = transpose_79)[name = tensor<string, []>("value_states_67_cast")]; |
| tensor<int32, [3]> var_1573_perm_0 = const()[name = tensor<string, []>("op_1573_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_97_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_97_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_97_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_97_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_77 = transpose(perm = var_1573_perm_0, x = key_states_67_cast)[name = tensor<string, []>("transpose_77")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_97_cast = matmul(transpose_x = attn_weights_97_transpose_x_0, transpose_y = attn_weights_97_transpose_y_0, x = query_states_33_cast, y = transpose_77)[name = tensor<string, []>("attn_weights_97_cast")]; |
| tensor<int32, [4]> var_1575 = const()[name = tensor<string, []>("op_1575"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_1576_cast = reshape(shape = var_1575, x = attn_weights_97_cast)[name = tensor<string, []>("op_1576_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_99_cast = add(x = var_1576_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_99_cast")]; |
| tensor<int32, [3]> var_1581 = const()[name = tensor<string, []>("op_1581"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_261_cast = reshape(shape = var_1581, x = attn_weights_99_cast)[name = tensor<string, []>("input_261_cast")]; |
| tensor<fp16, [20, 77, 77]> input_263_cast = softmax(axis = var_5, x = input_261_cast)[name = tensor<string, []>("input_263_cast")]; |
| 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 = matmul(transpose_x = attn_output_97_transpose_x_0, transpose_y = attn_output_97_transpose_y_0, x = input_263_cast, y = value_states_67_cast)[name = tensor<string, []>("attn_output_97_cast")]; |
| tensor<int32, [4]> var_1586 = const()[name = tensor<string, []>("op_1586"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_99_cast = reshape(shape = var_1586, x = attn_output_97_cast)[name = tensor<string, []>("attn_output_99_cast")]; |
| 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_1589 = const()[name = tensor<string, []>("op_1589"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_76 = transpose(perm = attn_output_101_perm_0, x = attn_output_99_cast)[name = tensor<string, []>("transpose_76")]; |
| tensor<fp16, [1, 77, 1280]> input_265_cast = reshape(shape = var_1589, x = transpose_76)[name = tensor<string, []>("input_265_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(766231936)))]; |
| 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, []>(769508800)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_99_cast = 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, x = input_265_cast)[name = tensor<string, []>("hidden_states_99_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_267_cast = add(x = input_259_cast, y = hidden_states_99_cast)[name = tensor<string, []>("input_267_cast")]; |
| 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, []>(769511424)))]; |
| 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, []>(769514048)))]; |
| tensor<fp16, [1, 77, 1280]> input_269_cast = 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)[name = tensor<string, []>("input_269_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(769516672)))]; |
| 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, []>(782623936)))]; |
| tensor<fp16, [1, 77, 5120]> input_271_cast = 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, x = input_269_cast)[name = tensor<string, []>("input_271_cast")]; |
| 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 = gelu(mode = input_273_mode_0, x = input_271_cast)[name = tensor<string, []>("input_273_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_16_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(782634240)))]; |
| 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, []>(795741504)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_101_cast = 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, x = input_273_cast)[name = tensor<string, []>("hidden_states_101_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_275_cast = add(x = input_267_cast, y = hidden_states_101_cast)[name = tensor<string, []>("input_275_cast")]; |
| 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, []>(795744128)))]; |
| 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, []>(795746752)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_103_cast = 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)[name = tensor<string, []>("hidden_states_103_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(795749376)))]; |
| 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, []>(799026240)))]; |
| tensor<fp16, [1, 77, 1280]> var_1627_cast = 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, x = hidden_states_103_cast)[name = tensor<string, []>("op_1627_cast")]; |
| tensor<fp16, []> var_1628_to_fp16 = const()[name = tensor<string, []>("op_1628_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_107_cast = mul(x = var_1627_cast, y = var_1628_to_fp16)[name = tensor<string, []>("tensor_107_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(799028864)))]; |
| 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, []>(802305728)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_103_cast = 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, x = hidden_states_103_cast)[name = tensor<string, []>("tensor_103_cast")]; |
| tensor<int32, [4]> var_1633 = const()[name = tensor<string, []>("op_1633"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1634_cast = reshape(shape = var_1633, x = tensor_103_cast)[name = tensor<string, []>("op_1634_cast")]; |
| tensor<int32, [4]> var_1635_perm_0 = const()[name = tensor<string, []>("op_1635_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(802308352)))]; |
| 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, []>(805585216)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_105_cast = 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, x = hidden_states_103_cast)[name = tensor<string, []>("tensor_105_cast")]; |
| tensor<int32, [4]> var_1640 = const()[name = tensor<string, []>("op_1640"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1641_cast = reshape(shape = var_1640, x = tensor_105_cast)[name = tensor<string, []>("op_1641_cast")]; |
| tensor<int32, [4]> var_1642_perm_0 = const()[name = tensor<string, []>("op_1642_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_1649 = const()[name = tensor<string, []>("op_1649"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1650_cast = reshape(shape = var_1649, x = tensor_107_cast)[name = tensor<string, []>("op_1650_cast")]; |
| tensor<int32, [4]> var_1651_perm_0 = const()[name = tensor<string, []>("op_1651_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_1653 = const()[name = tensor<string, []>("op_1653"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_73 = transpose(perm = var_1651_perm_0, x = var_1650_cast)[name = tensor<string, []>("transpose_73")]; |
| tensor<fp16, [20, 77, 64]> query_states_35_cast = reshape(shape = var_1653, x = transpose_73)[name = tensor<string, []>("query_states_35_cast")]; |
| tensor<int32, [3]> var_1655 = const()[name = tensor<string, []>("op_1655"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_75 = transpose(perm = var_1635_perm_0, x = var_1634_cast)[name = tensor<string, []>("transpose_75")]; |
| tensor<fp16, [20, 77, 64]> key_states_71_cast = reshape(shape = var_1655, x = transpose_75)[name = tensor<string, []>("key_states_71_cast")]; |
| tensor<int32, [3]> var_1657 = const()[name = tensor<string, []>("op_1657"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_74 = transpose(perm = var_1642_perm_0, x = var_1641_cast)[name = tensor<string, []>("transpose_74")]; |
| tensor<fp16, [20, 77, 64]> value_states_71_cast = reshape(shape = var_1657, x = transpose_74)[name = tensor<string, []>("value_states_71_cast")]; |
| tensor<int32, [3]> var_1660_perm_0 = const()[name = tensor<string, []>("op_1660_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_103_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_103_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_103_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_103_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_72 = transpose(perm = var_1660_perm_0, x = key_states_71_cast)[name = tensor<string, []>("transpose_72")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_103_cast = matmul(transpose_x = attn_weights_103_transpose_x_0, transpose_y = attn_weights_103_transpose_y_0, x = query_states_35_cast, y = transpose_72)[name = tensor<string, []>("attn_weights_103_cast")]; |
| tensor<int32, [4]> var_1662 = const()[name = tensor<string, []>("op_1662"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_1663_cast = reshape(shape = var_1662, x = attn_weights_103_cast)[name = tensor<string, []>("op_1663_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_105_cast = add(x = var_1663_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_105_cast")]; |
| tensor<int32, [3]> var_1668 = const()[name = tensor<string, []>("op_1668"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_277_cast = reshape(shape = var_1668, x = attn_weights_105_cast)[name = tensor<string, []>("input_277_cast")]; |
| tensor<fp16, [20, 77, 77]> input_279_cast = softmax(axis = var_5, x = input_277_cast)[name = tensor<string, []>("input_279_cast")]; |
| 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 = matmul(transpose_x = attn_output_103_transpose_x_0, transpose_y = attn_output_103_transpose_y_0, x = input_279_cast, y = value_states_71_cast)[name = tensor<string, []>("attn_output_103_cast")]; |
| tensor<int32, [4]> var_1673 = const()[name = tensor<string, []>("op_1673"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_105_cast = reshape(shape = var_1673, x = attn_output_103_cast)[name = tensor<string, []>("attn_output_105_cast")]; |
| 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_1676 = const()[name = tensor<string, []>("op_1676"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_71 = transpose(perm = attn_output_107_perm_0, x = attn_output_105_cast)[name = tensor<string, []>("transpose_71")]; |
| tensor<fp16, [1, 77, 1280]> input_281_cast = reshape(shape = var_1676, x = transpose_71)[name = tensor<string, []>("input_281_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(805587840)))]; |
| 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, []>(808864704)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_105_cast = 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, x = input_281_cast)[name = tensor<string, []>("hidden_states_105_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_283_cast = add(x = input_275_cast, y = hidden_states_105_cast)[name = tensor<string, []>("input_283_cast")]; |
| 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, []>(808867328)))]; |
| 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, []>(808869952)))]; |
| tensor<fp16, [1, 77, 1280]> input_285_cast = 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)[name = tensor<string, []>("input_285_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(808872576)))]; |
| 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, []>(821979840)))]; |
| tensor<fp16, [1, 77, 5120]> input_287_cast = 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, x = input_285_cast)[name = tensor<string, []>("input_287_cast")]; |
| 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 = gelu(mode = input_289_mode_0, x = input_287_cast)[name = tensor<string, []>("input_289_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_17_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(821990144)))]; |
| 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, []>(835097408)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_107_cast = 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, x = input_289_cast)[name = tensor<string, []>("hidden_states_107_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_291_cast = add(x = input_283_cast, y = hidden_states_107_cast)[name = tensor<string, []>("input_291_cast")]; |
| 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, []>(835100032)))]; |
| 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, []>(835102656)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_109_cast = 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)[name = tensor<string, []>("hidden_states_109_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(835105280)))]; |
| 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, []>(838382144)))]; |
| tensor<fp16, [1, 77, 1280]> var_1714_cast = 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, x = hidden_states_109_cast)[name = tensor<string, []>("op_1714_cast")]; |
| tensor<fp16, []> var_1715_to_fp16 = const()[name = tensor<string, []>("op_1715_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_113_cast = mul(x = var_1714_cast, y = var_1715_to_fp16)[name = tensor<string, []>("tensor_113_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(838384768)))]; |
| 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, []>(841661632)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_109_cast = 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, x = hidden_states_109_cast)[name = tensor<string, []>("tensor_109_cast")]; |
| tensor<int32, [4]> var_1720 = const()[name = tensor<string, []>("op_1720"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1721_cast = reshape(shape = var_1720, x = tensor_109_cast)[name = tensor<string, []>("op_1721_cast")]; |
| tensor<int32, [4]> var_1722_perm_0 = const()[name = tensor<string, []>("op_1722_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(841664256)))]; |
| 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, []>(844941120)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_111_cast = 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, x = hidden_states_109_cast)[name = tensor<string, []>("tensor_111_cast")]; |
| tensor<int32, [4]> var_1727 = const()[name = tensor<string, []>("op_1727"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1728_cast = reshape(shape = var_1727, x = tensor_111_cast)[name = tensor<string, []>("op_1728_cast")]; |
| tensor<int32, [4]> var_1729_perm_0 = const()[name = tensor<string, []>("op_1729_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_1736 = const()[name = tensor<string, []>("op_1736"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1737_cast = reshape(shape = var_1736, x = tensor_113_cast)[name = tensor<string, []>("op_1737_cast")]; |
| tensor<int32, [4]> var_1738_perm_0 = const()[name = tensor<string, []>("op_1738_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_1740 = const()[name = tensor<string, []>("op_1740"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_68 = transpose(perm = var_1738_perm_0, x = var_1737_cast)[name = tensor<string, []>("transpose_68")]; |
| tensor<fp16, [20, 77, 64]> query_states_37_cast = reshape(shape = var_1740, x = transpose_68)[name = tensor<string, []>("query_states_37_cast")]; |
| tensor<int32, [3]> var_1742 = const()[name = tensor<string, []>("op_1742"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_70 = transpose(perm = var_1722_perm_0, x = var_1721_cast)[name = tensor<string, []>("transpose_70")]; |
| tensor<fp16, [20, 77, 64]> key_states_75_cast = reshape(shape = var_1742, x = transpose_70)[name = tensor<string, []>("key_states_75_cast")]; |
| tensor<int32, [3]> var_1744 = const()[name = tensor<string, []>("op_1744"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_69 = transpose(perm = var_1729_perm_0, x = var_1728_cast)[name = tensor<string, []>("transpose_69")]; |
| tensor<fp16, [20, 77, 64]> value_states_75_cast = reshape(shape = var_1744, x = transpose_69)[name = tensor<string, []>("value_states_75_cast")]; |
| tensor<int32, [3]> var_1747_perm_0 = const()[name = tensor<string, []>("op_1747_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_109_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_109_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_109_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_109_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_67 = transpose(perm = var_1747_perm_0, x = key_states_75_cast)[name = tensor<string, []>("transpose_67")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_109_cast = matmul(transpose_x = attn_weights_109_transpose_x_0, transpose_y = attn_weights_109_transpose_y_0, x = query_states_37_cast, y = transpose_67)[name = tensor<string, []>("attn_weights_109_cast")]; |
| tensor<int32, [4]> var_1749 = const()[name = tensor<string, []>("op_1749"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_1750_cast = reshape(shape = var_1749, x = attn_weights_109_cast)[name = tensor<string, []>("op_1750_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_111_cast = add(x = var_1750_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_111_cast")]; |
| tensor<int32, [3]> var_1755 = const()[name = tensor<string, []>("op_1755"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_293_cast = reshape(shape = var_1755, x = attn_weights_111_cast)[name = tensor<string, []>("input_293_cast")]; |
| tensor<fp16, [20, 77, 77]> input_295_cast = softmax(axis = var_5, x = input_293_cast)[name = tensor<string, []>("input_295_cast")]; |
| 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 = matmul(transpose_x = attn_output_109_transpose_x_0, transpose_y = attn_output_109_transpose_y_0, x = input_295_cast, y = value_states_75_cast)[name = tensor<string, []>("attn_output_109_cast")]; |
| tensor<int32, [4]> var_1760 = const()[name = tensor<string, []>("op_1760"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_111_cast = reshape(shape = var_1760, x = attn_output_109_cast)[name = tensor<string, []>("attn_output_111_cast")]; |
| 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_1763 = const()[name = tensor<string, []>("op_1763"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_66 = transpose(perm = attn_output_113_perm_0, x = attn_output_111_cast)[name = tensor<string, []>("transpose_66")]; |
| tensor<fp16, [1, 77, 1280]> input_297_cast = reshape(shape = var_1763, x = transpose_66)[name = tensor<string, []>("input_297_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(844943744)))]; |
| 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, []>(848220608)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_111_cast = 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, x = input_297_cast)[name = tensor<string, []>("hidden_states_111_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_299_cast = add(x = input_291_cast, y = hidden_states_111_cast)[name = tensor<string, []>("input_299_cast")]; |
| 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, []>(848223232)))]; |
| 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, []>(848225856)))]; |
| tensor<fp16, [1, 77, 1280]> input_301_cast = 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)[name = tensor<string, []>("input_301_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(848228480)))]; |
| 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, []>(861335744)))]; |
| tensor<fp16, [1, 77, 5120]> input_303_cast = 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, x = input_301_cast)[name = tensor<string, []>("input_303_cast")]; |
| 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 = gelu(mode = input_305_mode_0, x = input_303_cast)[name = tensor<string, []>("input_305_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_18_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(861346048)))]; |
| 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, []>(874453312)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_113_cast = 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, x = input_305_cast)[name = tensor<string, []>("hidden_states_113_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_307_cast = add(x = input_299_cast, y = hidden_states_113_cast)[name = tensor<string, []>("input_307_cast")]; |
| 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, []>(874455936)))]; |
| 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, []>(874458560)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_115_cast = 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)[name = tensor<string, []>("hidden_states_115_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(874461184)))]; |
| 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, []>(877738048)))]; |
| tensor<fp16, [1, 77, 1280]> var_1801_cast = 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, x = hidden_states_115_cast)[name = tensor<string, []>("op_1801_cast")]; |
| tensor<fp16, []> var_1802_to_fp16 = const()[name = tensor<string, []>("op_1802_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_119_cast = mul(x = var_1801_cast, y = var_1802_to_fp16)[name = tensor<string, []>("tensor_119_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(877740672)))]; |
| 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, []>(881017536)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_115_cast = 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, x = hidden_states_115_cast)[name = tensor<string, []>("tensor_115_cast")]; |
| tensor<int32, [4]> var_1807 = const()[name = tensor<string, []>("op_1807"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1808_cast = reshape(shape = var_1807, x = tensor_115_cast)[name = tensor<string, []>("op_1808_cast")]; |
| tensor<int32, [4]> var_1809_perm_0 = const()[name = tensor<string, []>("op_1809_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(881020160)))]; |
| 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, []>(884297024)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_117_cast = 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, x = hidden_states_115_cast)[name = tensor<string, []>("tensor_117_cast")]; |
| tensor<int32, [4]> var_1814 = const()[name = tensor<string, []>("op_1814"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1815_cast = reshape(shape = var_1814, x = tensor_117_cast)[name = tensor<string, []>("op_1815_cast")]; |
| tensor<int32, [4]> var_1816_perm_0 = const()[name = tensor<string, []>("op_1816_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_1823 = const()[name = tensor<string, []>("op_1823"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1824_cast = reshape(shape = var_1823, x = tensor_119_cast)[name = tensor<string, []>("op_1824_cast")]; |
| tensor<int32, [4]> var_1825_perm_0 = const()[name = tensor<string, []>("op_1825_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_1827 = const()[name = tensor<string, []>("op_1827"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_63 = transpose(perm = var_1825_perm_0, x = var_1824_cast)[name = tensor<string, []>("transpose_63")]; |
| tensor<fp16, [20, 77, 64]> query_states_39_cast = reshape(shape = var_1827, x = transpose_63)[name = tensor<string, []>("query_states_39_cast")]; |
| tensor<int32, [3]> var_1829 = const()[name = tensor<string, []>("op_1829"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_65 = transpose(perm = var_1809_perm_0, x = var_1808_cast)[name = tensor<string, []>("transpose_65")]; |
| tensor<fp16, [20, 77, 64]> key_states_79_cast = reshape(shape = var_1829, x = transpose_65)[name = tensor<string, []>("key_states_79_cast")]; |
| tensor<int32, [3]> var_1831 = const()[name = tensor<string, []>("op_1831"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_64 = transpose(perm = var_1816_perm_0, x = var_1815_cast)[name = tensor<string, []>("transpose_64")]; |
| tensor<fp16, [20, 77, 64]> value_states_79_cast = reshape(shape = var_1831, x = transpose_64)[name = tensor<string, []>("value_states_79_cast")]; |
| tensor<int32, [3]> var_1834_perm_0 = const()[name = tensor<string, []>("op_1834_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_115_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_115_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_115_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_115_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_62 = transpose(perm = var_1834_perm_0, x = key_states_79_cast)[name = tensor<string, []>("transpose_62")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_115_cast = matmul(transpose_x = attn_weights_115_transpose_x_0, transpose_y = attn_weights_115_transpose_y_0, x = query_states_39_cast, y = transpose_62)[name = tensor<string, []>("attn_weights_115_cast")]; |
| tensor<int32, [4]> var_1836 = const()[name = tensor<string, []>("op_1836"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_1837_cast = reshape(shape = var_1836, x = attn_weights_115_cast)[name = tensor<string, []>("op_1837_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_117_cast = add(x = var_1837_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_117_cast")]; |
| tensor<int32, [3]> var_1842 = const()[name = tensor<string, []>("op_1842"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_309_cast = reshape(shape = var_1842, x = attn_weights_117_cast)[name = tensor<string, []>("input_309_cast")]; |
| tensor<fp16, [20, 77, 77]> input_311_cast = softmax(axis = var_5, x = input_309_cast)[name = tensor<string, []>("input_311_cast")]; |
| 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 = matmul(transpose_x = attn_output_115_transpose_x_0, transpose_y = attn_output_115_transpose_y_0, x = input_311_cast, y = value_states_79_cast)[name = tensor<string, []>("attn_output_115_cast")]; |
| tensor<int32, [4]> var_1847 = const()[name = tensor<string, []>("op_1847"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_117_cast = reshape(shape = var_1847, x = attn_output_115_cast)[name = tensor<string, []>("attn_output_117_cast")]; |
| 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_1850 = const()[name = tensor<string, []>("op_1850"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_61 = transpose(perm = attn_output_119_perm_0, x = attn_output_117_cast)[name = tensor<string, []>("transpose_61")]; |
| tensor<fp16, [1, 77, 1280]> input_313_cast = reshape(shape = var_1850, x = transpose_61)[name = tensor<string, []>("input_313_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(884299648)))]; |
| 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, []>(887576512)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_117_cast = 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, x = input_313_cast)[name = tensor<string, []>("hidden_states_117_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_315_cast = add(x = input_307_cast, y = hidden_states_117_cast)[name = tensor<string, []>("input_315_cast")]; |
| 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, []>(887579136)))]; |
| 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, []>(887581760)))]; |
| tensor<fp16, [1, 77, 1280]> input_317_cast = 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)[name = tensor<string, []>("input_317_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(887584384)))]; |
| 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, []>(900691648)))]; |
| tensor<fp16, [1, 77, 5120]> input_319_cast = 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, x = input_317_cast)[name = tensor<string, []>("input_319_cast")]; |
| 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 = gelu(mode = input_321_mode_0, x = input_319_cast)[name = tensor<string, []>("input_321_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_19_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(900701952)))]; |
| 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, []>(913809216)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_119_cast = 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, x = input_321_cast)[name = tensor<string, []>("hidden_states_119_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_323_cast = add(x = input_315_cast, y = hidden_states_119_cast)[name = tensor<string, []>("input_323_cast")]; |
| 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, []>(913811840)))]; |
| 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, []>(913814464)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_121_cast = 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)[name = tensor<string, []>("hidden_states_121_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(913817088)))]; |
| 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, []>(917093952)))]; |
| tensor<fp16, [1, 77, 1280]> var_1888_cast = 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, x = hidden_states_121_cast)[name = tensor<string, []>("op_1888_cast")]; |
| tensor<fp16, []> var_1889_to_fp16 = const()[name = tensor<string, []>("op_1889_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_125_cast = mul(x = var_1888_cast, y = var_1889_to_fp16)[name = tensor<string, []>("tensor_125_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(917096576)))]; |
| 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, []>(920373440)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_121_cast = 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, x = hidden_states_121_cast)[name = tensor<string, []>("tensor_121_cast")]; |
| tensor<int32, [4]> var_1894 = const()[name = tensor<string, []>("op_1894"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1895_cast = reshape(shape = var_1894, x = tensor_121_cast)[name = tensor<string, []>("op_1895_cast")]; |
| tensor<int32, [4]> var_1896_perm_0 = const()[name = tensor<string, []>("op_1896_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(920376064)))]; |
| 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, []>(923652928)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_123_cast = 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, x = hidden_states_121_cast)[name = tensor<string, []>("tensor_123_cast")]; |
| tensor<int32, [4]> var_1901 = const()[name = tensor<string, []>("op_1901"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1902_cast = reshape(shape = var_1901, x = tensor_123_cast)[name = tensor<string, []>("op_1902_cast")]; |
| tensor<int32, [4]> var_1903_perm_0 = const()[name = tensor<string, []>("op_1903_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_1910 = const()[name = tensor<string, []>("op_1910"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1911_cast = reshape(shape = var_1910, x = tensor_125_cast)[name = tensor<string, []>("op_1911_cast")]; |
| tensor<int32, [4]> var_1912_perm_0 = const()[name = tensor<string, []>("op_1912_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_1914 = const()[name = tensor<string, []>("op_1914"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_58 = transpose(perm = var_1912_perm_0, x = var_1911_cast)[name = tensor<string, []>("transpose_58")]; |
| tensor<fp16, [20, 77, 64]> query_states_41_cast = reshape(shape = var_1914, x = transpose_58)[name = tensor<string, []>("query_states_41_cast")]; |
| tensor<int32, [3]> var_1916 = const()[name = tensor<string, []>("op_1916"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_60 = transpose(perm = var_1896_perm_0, x = var_1895_cast)[name = tensor<string, []>("transpose_60")]; |
| tensor<fp16, [20, 77, 64]> key_states_83_cast = reshape(shape = var_1916, x = transpose_60)[name = tensor<string, []>("key_states_83_cast")]; |
| tensor<int32, [3]> var_1918 = const()[name = tensor<string, []>("op_1918"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_59 = transpose(perm = var_1903_perm_0, x = var_1902_cast)[name = tensor<string, []>("transpose_59")]; |
| tensor<fp16, [20, 77, 64]> value_states_83_cast = reshape(shape = var_1918, x = transpose_59)[name = tensor<string, []>("value_states_83_cast")]; |
| tensor<int32, [3]> var_1921_perm_0 = const()[name = tensor<string, []>("op_1921_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_121_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_121_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_121_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_121_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_57 = transpose(perm = var_1921_perm_0, x = key_states_83_cast)[name = tensor<string, []>("transpose_57")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_121_cast = matmul(transpose_x = attn_weights_121_transpose_x_0, transpose_y = attn_weights_121_transpose_y_0, x = query_states_41_cast, y = transpose_57)[name = tensor<string, []>("attn_weights_121_cast")]; |
| tensor<int32, [4]> var_1923 = const()[name = tensor<string, []>("op_1923"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_1924_cast = reshape(shape = var_1923, x = attn_weights_121_cast)[name = tensor<string, []>("op_1924_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_123_cast = add(x = var_1924_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_123_cast")]; |
| tensor<int32, [3]> var_1929 = const()[name = tensor<string, []>("op_1929"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_325_cast = reshape(shape = var_1929, x = attn_weights_123_cast)[name = tensor<string, []>("input_325_cast")]; |
| tensor<fp16, [20, 77, 77]> input_327_cast = softmax(axis = var_5, x = input_325_cast)[name = tensor<string, []>("input_327_cast")]; |
| 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 = matmul(transpose_x = attn_output_121_transpose_x_0, transpose_y = attn_output_121_transpose_y_0, x = input_327_cast, y = value_states_83_cast)[name = tensor<string, []>("attn_output_121_cast")]; |
| tensor<int32, [4]> var_1934 = const()[name = tensor<string, []>("op_1934"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_123_cast = reshape(shape = var_1934, x = attn_output_121_cast)[name = tensor<string, []>("attn_output_123_cast")]; |
| 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_1937 = const()[name = tensor<string, []>("op_1937"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_56 = transpose(perm = attn_output_125_perm_0, x = attn_output_123_cast)[name = tensor<string, []>("transpose_56")]; |
| tensor<fp16, [1, 77, 1280]> input_329_cast = reshape(shape = var_1937, x = transpose_56)[name = tensor<string, []>("input_329_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(923655552)))]; |
| 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, []>(926932416)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_123_cast = 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, x = input_329_cast)[name = tensor<string, []>("hidden_states_123_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_331_cast = add(x = input_323_cast, y = hidden_states_123_cast)[name = tensor<string, []>("input_331_cast")]; |
| 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, []>(926935040)))]; |
| 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, []>(926937664)))]; |
| tensor<fp16, [1, 77, 1280]> input_333_cast = 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)[name = tensor<string, []>("input_333_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(926940288)))]; |
| 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, []>(940047552)))]; |
| tensor<fp16, [1, 77, 5120]> input_335_cast = 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, x = input_333_cast)[name = tensor<string, []>("input_335_cast")]; |
| 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 = gelu(mode = input_337_mode_0, x = input_335_cast)[name = tensor<string, []>("input_337_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_20_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(940057856)))]; |
| 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, []>(953165120)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_125_cast = 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, x = input_337_cast)[name = tensor<string, []>("hidden_states_125_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_339_cast = add(x = input_331_cast, y = hidden_states_125_cast)[name = tensor<string, []>("input_339_cast")]; |
| 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, []>(953167744)))]; |
| 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, []>(953170368)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_127_cast = 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)[name = tensor<string, []>("hidden_states_127_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(953172992)))]; |
| 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, []>(956449856)))]; |
| tensor<fp16, [1, 77, 1280]> var_1975_cast = 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, x = hidden_states_127_cast)[name = tensor<string, []>("op_1975_cast")]; |
| tensor<fp16, []> var_1976_to_fp16 = const()[name = tensor<string, []>("op_1976_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_131_cast = mul(x = var_1975_cast, y = var_1976_to_fp16)[name = tensor<string, []>("tensor_131_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(956452480)))]; |
| 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, []>(959729344)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_127_cast = 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, x = hidden_states_127_cast)[name = tensor<string, []>("tensor_127_cast")]; |
| tensor<int32, [4]> var_1981 = const()[name = tensor<string, []>("op_1981"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1982_cast = reshape(shape = var_1981, x = tensor_127_cast)[name = tensor<string, []>("op_1982_cast")]; |
| tensor<int32, [4]> var_1983_perm_0 = const()[name = tensor<string, []>("op_1983_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(959731968)))]; |
| 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, []>(963008832)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_129_cast = 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, x = hidden_states_127_cast)[name = tensor<string, []>("tensor_129_cast")]; |
| tensor<int32, [4]> var_1988 = const()[name = tensor<string, []>("op_1988"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1989_cast = reshape(shape = var_1988, x = tensor_129_cast)[name = tensor<string, []>("op_1989_cast")]; |
| tensor<int32, [4]> var_1990_perm_0 = const()[name = tensor<string, []>("op_1990_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_1997 = const()[name = tensor<string, []>("op_1997"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_1998_cast = reshape(shape = var_1997, x = tensor_131_cast)[name = tensor<string, []>("op_1998_cast")]; |
| tensor<int32, [4]> var_1999_perm_0 = const()[name = tensor<string, []>("op_1999_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_2001 = const()[name = tensor<string, []>("op_2001"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_53 = transpose(perm = var_1999_perm_0, x = var_1998_cast)[name = tensor<string, []>("transpose_53")]; |
| tensor<fp16, [20, 77, 64]> query_states_43_cast = reshape(shape = var_2001, x = transpose_53)[name = tensor<string, []>("query_states_43_cast")]; |
| tensor<int32, [3]> var_2003 = const()[name = tensor<string, []>("op_2003"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_55 = transpose(perm = var_1983_perm_0, x = var_1982_cast)[name = tensor<string, []>("transpose_55")]; |
| tensor<fp16, [20, 77, 64]> key_states_87_cast = reshape(shape = var_2003, x = transpose_55)[name = tensor<string, []>("key_states_87_cast")]; |
| tensor<int32, [3]> var_2005 = const()[name = tensor<string, []>("op_2005"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_54 = transpose(perm = var_1990_perm_0, x = var_1989_cast)[name = tensor<string, []>("transpose_54")]; |
| tensor<fp16, [20, 77, 64]> value_states_87_cast = reshape(shape = var_2005, x = transpose_54)[name = tensor<string, []>("value_states_87_cast")]; |
| tensor<int32, [3]> var_2008_perm_0 = const()[name = tensor<string, []>("op_2008_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_127_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_127_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_127_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_127_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_52 = transpose(perm = var_2008_perm_0, x = key_states_87_cast)[name = tensor<string, []>("transpose_52")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_127_cast = matmul(transpose_x = attn_weights_127_transpose_x_0, transpose_y = attn_weights_127_transpose_y_0, x = query_states_43_cast, y = transpose_52)[name = tensor<string, []>("attn_weights_127_cast")]; |
| tensor<int32, [4]> var_2010 = const()[name = tensor<string, []>("op_2010"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_2011_cast = reshape(shape = var_2010, x = attn_weights_127_cast)[name = tensor<string, []>("op_2011_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_129_cast = add(x = var_2011_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_129_cast")]; |
| tensor<int32, [3]> var_2016 = const()[name = tensor<string, []>("op_2016"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_341_cast = reshape(shape = var_2016, x = attn_weights_129_cast)[name = tensor<string, []>("input_341_cast")]; |
| tensor<fp16, [20, 77, 77]> input_343_cast = softmax(axis = var_5, x = input_341_cast)[name = tensor<string, []>("input_343_cast")]; |
| 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 = matmul(transpose_x = attn_output_127_transpose_x_0, transpose_y = attn_output_127_transpose_y_0, x = input_343_cast, y = value_states_87_cast)[name = tensor<string, []>("attn_output_127_cast")]; |
| tensor<int32, [4]> var_2021 = const()[name = tensor<string, []>("op_2021"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_129_cast = reshape(shape = var_2021, x = attn_output_127_cast)[name = tensor<string, []>("attn_output_129_cast")]; |
| 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_2024 = const()[name = tensor<string, []>("op_2024"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_51 = transpose(perm = attn_output_131_perm_0, x = attn_output_129_cast)[name = tensor<string, []>("transpose_51")]; |
| tensor<fp16, [1, 77, 1280]> input_345_cast = reshape(shape = var_2024, x = transpose_51)[name = tensor<string, []>("input_345_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(963011456)))]; |
| 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, []>(966288320)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_129_cast = 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, x = input_345_cast)[name = tensor<string, []>("hidden_states_129_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_347_cast = add(x = input_339_cast, y = hidden_states_129_cast)[name = tensor<string, []>("input_347_cast")]; |
| 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, []>(966290944)))]; |
| 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, []>(966293568)))]; |
| tensor<fp16, [1, 77, 1280]> input_349_cast = 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)[name = tensor<string, []>("input_349_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(966296192)))]; |
| 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, []>(979403456)))]; |
| tensor<fp16, [1, 77, 5120]> input_351_cast = 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, x = input_349_cast)[name = tensor<string, []>("input_351_cast")]; |
| 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 = gelu(mode = input_353_mode_0, x = input_351_cast)[name = tensor<string, []>("input_353_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_21_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(979413760)))]; |
| 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, []>(992521024)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_131_cast = 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, x = input_353_cast)[name = tensor<string, []>("hidden_states_131_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_355_cast = add(x = input_347_cast, y = hidden_states_131_cast)[name = tensor<string, []>("input_355_cast")]; |
| 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, []>(992523648)))]; |
| 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, []>(992526272)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_133_cast = 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)[name = tensor<string, []>("hidden_states_133_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(992528896)))]; |
| 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, []>(995805760)))]; |
| tensor<fp16, [1, 77, 1280]> var_2062_cast = 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, x = hidden_states_133_cast)[name = tensor<string, []>("op_2062_cast")]; |
| tensor<fp16, []> var_2063_to_fp16 = const()[name = tensor<string, []>("op_2063_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_137_cast = mul(x = var_2062_cast, y = var_2063_to_fp16)[name = tensor<string, []>("tensor_137_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(995808384)))]; |
| 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, []>(999085248)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_133_cast = 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, x = hidden_states_133_cast)[name = tensor<string, []>("tensor_133_cast")]; |
| tensor<int32, [4]> var_2068 = const()[name = tensor<string, []>("op_2068"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2069_cast = reshape(shape = var_2068, x = tensor_133_cast)[name = tensor<string, []>("op_2069_cast")]; |
| tensor<int32, [4]> var_2070_perm_0 = const()[name = tensor<string, []>("op_2070_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(999087872)))]; |
| 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, []>(1002364736)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_135_cast = 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, x = hidden_states_133_cast)[name = tensor<string, []>("tensor_135_cast")]; |
| tensor<int32, [4]> var_2075 = const()[name = tensor<string, []>("op_2075"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2076_cast = reshape(shape = var_2075, x = tensor_135_cast)[name = tensor<string, []>("op_2076_cast")]; |
| tensor<int32, [4]> var_2077_perm_0 = const()[name = tensor<string, []>("op_2077_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_2084 = const()[name = tensor<string, []>("op_2084"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2085_cast = reshape(shape = var_2084, x = tensor_137_cast)[name = tensor<string, []>("op_2085_cast")]; |
| tensor<int32, [4]> var_2086_perm_0 = const()[name = tensor<string, []>("op_2086_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_2088 = const()[name = tensor<string, []>("op_2088"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_48 = transpose(perm = var_2086_perm_0, x = var_2085_cast)[name = tensor<string, []>("transpose_48")]; |
| tensor<fp16, [20, 77, 64]> query_states_45_cast = reshape(shape = var_2088, x = transpose_48)[name = tensor<string, []>("query_states_45_cast")]; |
| tensor<int32, [3]> var_2090 = const()[name = tensor<string, []>("op_2090"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_50 = transpose(perm = var_2070_perm_0, x = var_2069_cast)[name = tensor<string, []>("transpose_50")]; |
| tensor<fp16, [20, 77, 64]> key_states_91_cast = reshape(shape = var_2090, x = transpose_50)[name = tensor<string, []>("key_states_91_cast")]; |
| tensor<int32, [3]> var_2092 = const()[name = tensor<string, []>("op_2092"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_49 = transpose(perm = var_2077_perm_0, x = var_2076_cast)[name = tensor<string, []>("transpose_49")]; |
| tensor<fp16, [20, 77, 64]> value_states_91_cast = reshape(shape = var_2092, x = transpose_49)[name = tensor<string, []>("value_states_91_cast")]; |
| tensor<int32, [3]> var_2095_perm_0 = const()[name = tensor<string, []>("op_2095_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_133_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_133_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_133_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_133_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_47 = transpose(perm = var_2095_perm_0, x = key_states_91_cast)[name = tensor<string, []>("transpose_47")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_133_cast = matmul(transpose_x = attn_weights_133_transpose_x_0, transpose_y = attn_weights_133_transpose_y_0, x = query_states_45_cast, y = transpose_47)[name = tensor<string, []>("attn_weights_133_cast")]; |
| tensor<int32, [4]> var_2097 = const()[name = tensor<string, []>("op_2097"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_2098_cast = reshape(shape = var_2097, x = attn_weights_133_cast)[name = tensor<string, []>("op_2098_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_135_cast = add(x = var_2098_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_135_cast")]; |
| tensor<int32, [3]> var_2103 = const()[name = tensor<string, []>("op_2103"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_357_cast = reshape(shape = var_2103, x = attn_weights_135_cast)[name = tensor<string, []>("input_357_cast")]; |
| tensor<fp16, [20, 77, 77]> input_359_cast = softmax(axis = var_5, x = input_357_cast)[name = tensor<string, []>("input_359_cast")]; |
| 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 = matmul(transpose_x = attn_output_133_transpose_x_0, transpose_y = attn_output_133_transpose_y_0, x = input_359_cast, y = value_states_91_cast)[name = tensor<string, []>("attn_output_133_cast")]; |
| tensor<int32, [4]> var_2108 = const()[name = tensor<string, []>("op_2108"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_135_cast = reshape(shape = var_2108, x = attn_output_133_cast)[name = tensor<string, []>("attn_output_135_cast")]; |
| 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_2111 = const()[name = tensor<string, []>("op_2111"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_46 = transpose(perm = attn_output_137_perm_0, x = attn_output_135_cast)[name = tensor<string, []>("transpose_46")]; |
| tensor<fp16, [1, 77, 1280]> input_361_cast = reshape(shape = var_2111, x = transpose_46)[name = tensor<string, []>("input_361_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1002367360)))]; |
| 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, []>(1005644224)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_135_cast = 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, x = input_361_cast)[name = tensor<string, []>("hidden_states_135_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_363_cast = add(x = input_355_cast, y = hidden_states_135_cast)[name = tensor<string, []>("input_363_cast")]; |
| 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, []>(1005646848)))]; |
| 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, []>(1005649472)))]; |
| tensor<fp16, [1, 77, 1280]> input_365_cast = 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)[name = tensor<string, []>("input_365_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1005652096)))]; |
| 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, []>(1018759360)))]; |
| tensor<fp16, [1, 77, 5120]> input_367_cast = 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, x = input_365_cast)[name = tensor<string, []>("input_367_cast")]; |
| 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 = gelu(mode = input_369_mode_0, x = input_367_cast)[name = tensor<string, []>("input_369_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_22_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1018769664)))]; |
| 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, []>(1031876928)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_137_cast = 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, x = input_369_cast)[name = tensor<string, []>("hidden_states_137_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_371_cast = add(x = input_363_cast, y = hidden_states_137_cast)[name = tensor<string, []>("input_371_cast")]; |
| 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, []>(1031879552)))]; |
| 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, []>(1031882176)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_139_cast = 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)[name = tensor<string, []>("hidden_states_139_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_23_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1031884800)))]; |
| 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, []>(1035161664)))]; |
| tensor<fp16, [1, 77, 1280]> var_2149_cast = 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, x = hidden_states_139_cast)[name = tensor<string, []>("op_2149_cast")]; |
| tensor<fp16, []> var_2150_to_fp16 = const()[name = tensor<string, []>("op_2150_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_143_cast = mul(x = var_2149_cast, y = var_2150_to_fp16)[name = tensor<string, []>("tensor_143_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_23_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1035164288)))]; |
| 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, []>(1038441152)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_139_cast = 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, x = hidden_states_139_cast)[name = tensor<string, []>("tensor_139_cast")]; |
| tensor<int32, [4]> var_2155 = const()[name = tensor<string, []>("op_2155"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2156_cast = reshape(shape = var_2155, x = tensor_139_cast)[name = tensor<string, []>("op_2156_cast")]; |
| tensor<int32, [4]> var_2157_perm_0 = const()[name = tensor<string, []>("op_2157_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1038443776)))]; |
| 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, []>(1041720640)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_141_cast = 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, x = hidden_states_139_cast)[name = tensor<string, []>("tensor_141_cast")]; |
| tensor<int32, [4]> var_2162 = const()[name = tensor<string, []>("op_2162"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2163_cast = reshape(shape = var_2162, x = tensor_141_cast)[name = tensor<string, []>("op_2163_cast")]; |
| tensor<int32, [4]> var_2164_perm_0 = const()[name = tensor<string, []>("op_2164_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_2171 = const()[name = tensor<string, []>("op_2171"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2172_cast = reshape(shape = var_2171, x = tensor_143_cast)[name = tensor<string, []>("op_2172_cast")]; |
| tensor<int32, [4]> var_2173_perm_0 = const()[name = tensor<string, []>("op_2173_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_2175 = const()[name = tensor<string, []>("op_2175"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_43 = transpose(perm = var_2173_perm_0, x = var_2172_cast)[name = tensor<string, []>("transpose_43")]; |
| tensor<fp16, [20, 77, 64]> query_states_47_cast = reshape(shape = var_2175, x = transpose_43)[name = tensor<string, []>("query_states_47_cast")]; |
| tensor<int32, [3]> var_2177 = const()[name = tensor<string, []>("op_2177"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_45 = transpose(perm = var_2157_perm_0, x = var_2156_cast)[name = tensor<string, []>("transpose_45")]; |
| tensor<fp16, [20, 77, 64]> key_states_95_cast = reshape(shape = var_2177, x = transpose_45)[name = tensor<string, []>("key_states_95_cast")]; |
| tensor<int32, [3]> var_2179 = const()[name = tensor<string, []>("op_2179"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_44 = transpose(perm = var_2164_perm_0, x = var_2163_cast)[name = tensor<string, []>("transpose_44")]; |
| tensor<fp16, [20, 77, 64]> value_states_95_cast = reshape(shape = var_2179, x = transpose_44)[name = tensor<string, []>("value_states_95_cast")]; |
| tensor<int32, [3]> var_2182_perm_0 = const()[name = tensor<string, []>("op_2182_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_139_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_139_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_139_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_139_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_42 = transpose(perm = var_2182_perm_0, x = key_states_95_cast)[name = tensor<string, []>("transpose_42")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_139_cast = matmul(transpose_x = attn_weights_139_transpose_x_0, transpose_y = attn_weights_139_transpose_y_0, x = query_states_47_cast, y = transpose_42)[name = tensor<string, []>("attn_weights_139_cast")]; |
| tensor<int32, [4]> var_2184 = const()[name = tensor<string, []>("op_2184"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_2185_cast = reshape(shape = var_2184, x = attn_weights_139_cast)[name = tensor<string, []>("op_2185_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_141_cast = add(x = var_2185_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_141_cast")]; |
| tensor<int32, [3]> var_2190 = const()[name = tensor<string, []>("op_2190"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_373_cast = reshape(shape = var_2190, x = attn_weights_141_cast)[name = tensor<string, []>("input_373_cast")]; |
| tensor<fp16, [20, 77, 77]> input_375_cast = softmax(axis = var_5, x = input_373_cast)[name = tensor<string, []>("input_375_cast")]; |
| 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 = matmul(transpose_x = attn_output_139_transpose_x_0, transpose_y = attn_output_139_transpose_y_0, x = input_375_cast, y = value_states_95_cast)[name = tensor<string, []>("attn_output_139_cast")]; |
| tensor<int32, [4]> var_2195 = const()[name = tensor<string, []>("op_2195"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_141_cast = reshape(shape = var_2195, x = attn_output_139_cast)[name = tensor<string, []>("attn_output_141_cast")]; |
| 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_2198 = const()[name = tensor<string, []>("op_2198"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_41 = transpose(perm = attn_output_143_perm_0, x = attn_output_141_cast)[name = tensor<string, []>("transpose_41")]; |
| tensor<fp16, [1, 77, 1280]> input_377_cast = reshape(shape = var_2198, x = transpose_41)[name = tensor<string, []>("input_377_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_23_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1041723264)))]; |
| 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, []>(1045000128)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_141_cast = 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, x = input_377_cast)[name = tensor<string, []>("hidden_states_141_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_379_cast = add(x = input_371_cast, y = hidden_states_141_cast)[name = tensor<string, []>("input_379_cast")]; |
| 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, []>(1045002752)))]; |
| 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, []>(1045005376)))]; |
| tensor<fp16, [1, 77, 1280]> input_381_cast = 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)[name = tensor<string, []>("input_381_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_23_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1045008000)))]; |
| 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, []>(1058115264)))]; |
| tensor<fp16, [1, 77, 5120]> input_383_cast = 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, x = input_381_cast)[name = tensor<string, []>("input_383_cast")]; |
| 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 = gelu(mode = input_385_mode_0, x = input_383_cast)[name = tensor<string, []>("input_385_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_23_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1058125568)))]; |
| 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, []>(1071232832)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_143_cast = 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, x = input_385_cast)[name = tensor<string, []>("hidden_states_143_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_387_cast = add(x = input_379_cast, y = hidden_states_143_cast)[name = tensor<string, []>("input_387_cast")]; |
| 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, []>(1071235456)))]; |
| 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, []>(1071238080)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_145_cast = 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)[name = tensor<string, []>("hidden_states_145_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_24_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1071240704)))]; |
| 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, []>(1074517568)))]; |
| tensor<fp16, [1, 77, 1280]> var_2236_cast = 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, x = hidden_states_145_cast)[name = tensor<string, []>("op_2236_cast")]; |
| tensor<fp16, []> var_2237_to_fp16 = const()[name = tensor<string, []>("op_2237_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_149_cast = mul(x = var_2236_cast, y = var_2237_to_fp16)[name = tensor<string, []>("tensor_149_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_24_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1074520192)))]; |
| 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, []>(1077797056)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_145_cast = 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, x = hidden_states_145_cast)[name = tensor<string, []>("tensor_145_cast")]; |
| tensor<int32, [4]> var_2242 = const()[name = tensor<string, []>("op_2242"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2243_cast = reshape(shape = var_2242, x = tensor_145_cast)[name = tensor<string, []>("op_2243_cast")]; |
| tensor<int32, [4]> var_2244_perm_0 = const()[name = tensor<string, []>("op_2244_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1077799680)))]; |
| 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, []>(1081076544)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_147_cast = 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, x = hidden_states_145_cast)[name = tensor<string, []>("tensor_147_cast")]; |
| tensor<int32, [4]> var_2249 = const()[name = tensor<string, []>("op_2249"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2250_cast = reshape(shape = var_2249, x = tensor_147_cast)[name = tensor<string, []>("op_2250_cast")]; |
| tensor<int32, [4]> var_2251_perm_0 = const()[name = tensor<string, []>("op_2251_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_2258 = const()[name = tensor<string, []>("op_2258"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2259_cast = reshape(shape = var_2258, x = tensor_149_cast)[name = tensor<string, []>("op_2259_cast")]; |
| tensor<int32, [4]> var_2260_perm_0 = const()[name = tensor<string, []>("op_2260_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_2262 = const()[name = tensor<string, []>("op_2262"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_38 = transpose(perm = var_2260_perm_0, x = var_2259_cast)[name = tensor<string, []>("transpose_38")]; |
| tensor<fp16, [20, 77, 64]> query_states_49_cast = reshape(shape = var_2262, x = transpose_38)[name = tensor<string, []>("query_states_49_cast")]; |
| tensor<int32, [3]> var_2264 = const()[name = tensor<string, []>("op_2264"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_40 = transpose(perm = var_2244_perm_0, x = var_2243_cast)[name = tensor<string, []>("transpose_40")]; |
| tensor<fp16, [20, 77, 64]> key_states_99_cast = reshape(shape = var_2264, x = transpose_40)[name = tensor<string, []>("key_states_99_cast")]; |
| tensor<int32, [3]> var_2266 = const()[name = tensor<string, []>("op_2266"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_39 = transpose(perm = var_2251_perm_0, x = var_2250_cast)[name = tensor<string, []>("transpose_39")]; |
| tensor<fp16, [20, 77, 64]> value_states_99_cast = reshape(shape = var_2266, x = transpose_39)[name = tensor<string, []>("value_states_99_cast")]; |
| tensor<int32, [3]> var_2269_perm_0 = const()[name = tensor<string, []>("op_2269_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_145_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_145_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_145_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_145_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_37 = transpose(perm = var_2269_perm_0, x = key_states_99_cast)[name = tensor<string, []>("transpose_37")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_145_cast = matmul(transpose_x = attn_weights_145_transpose_x_0, transpose_y = attn_weights_145_transpose_y_0, x = query_states_49_cast, y = transpose_37)[name = tensor<string, []>("attn_weights_145_cast")]; |
| tensor<int32, [4]> var_2271 = const()[name = tensor<string, []>("op_2271"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_2272_cast = reshape(shape = var_2271, x = attn_weights_145_cast)[name = tensor<string, []>("op_2272_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_147_cast = add(x = var_2272_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_147_cast")]; |
| tensor<int32, [3]> var_2277 = const()[name = tensor<string, []>("op_2277"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_389_cast = reshape(shape = var_2277, x = attn_weights_147_cast)[name = tensor<string, []>("input_389_cast")]; |
| tensor<fp16, [20, 77, 77]> input_391_cast = softmax(axis = var_5, x = input_389_cast)[name = tensor<string, []>("input_391_cast")]; |
| 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 = matmul(transpose_x = attn_output_145_transpose_x_0, transpose_y = attn_output_145_transpose_y_0, x = input_391_cast, y = value_states_99_cast)[name = tensor<string, []>("attn_output_145_cast")]; |
| tensor<int32, [4]> var_2282 = const()[name = tensor<string, []>("op_2282"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_147_cast = reshape(shape = var_2282, x = attn_output_145_cast)[name = tensor<string, []>("attn_output_147_cast")]; |
| 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_2285 = const()[name = tensor<string, []>("op_2285"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_36 = transpose(perm = attn_output_149_perm_0, x = attn_output_147_cast)[name = tensor<string, []>("transpose_36")]; |
| tensor<fp16, [1, 77, 1280]> input_393_cast = reshape(shape = var_2285, x = transpose_36)[name = tensor<string, []>("input_393_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_24_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1081079168)))]; |
| 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, []>(1084356032)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_147_cast = 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, x = input_393_cast)[name = tensor<string, []>("hidden_states_147_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_395_cast = add(x = input_387_cast, y = hidden_states_147_cast)[name = tensor<string, []>("input_395_cast")]; |
| 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, []>(1084358656)))]; |
| 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, []>(1084361280)))]; |
| tensor<fp16, [1, 77, 1280]> input_397_cast = 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)[name = tensor<string, []>("input_397_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_24_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1084363904)))]; |
| 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, []>(1097471168)))]; |
| tensor<fp16, [1, 77, 5120]> input_399_cast = 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, x = input_397_cast)[name = tensor<string, []>("input_399_cast")]; |
| 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 = gelu(mode = input_401_mode_0, x = input_399_cast)[name = tensor<string, []>("input_401_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_24_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1097481472)))]; |
| 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, []>(1110588736)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_149_cast = 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, x = input_401_cast)[name = tensor<string, []>("hidden_states_149_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_403_cast = add(x = input_395_cast, y = hidden_states_149_cast)[name = tensor<string, []>("input_403_cast")]; |
| 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, []>(1110591360)))]; |
| 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, []>(1110593984)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_151_cast = 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)[name = tensor<string, []>("hidden_states_151_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_25_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1110596608)))]; |
| 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, []>(1113873472)))]; |
| tensor<fp16, [1, 77, 1280]> var_2323_cast = 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, x = hidden_states_151_cast)[name = tensor<string, []>("op_2323_cast")]; |
| tensor<fp16, []> var_2324_to_fp16 = const()[name = tensor<string, []>("op_2324_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_155_cast = mul(x = var_2323_cast, y = var_2324_to_fp16)[name = tensor<string, []>("tensor_155_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_25_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1113876096)))]; |
| 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, []>(1117152960)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_151_cast = 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, x = hidden_states_151_cast)[name = tensor<string, []>("tensor_151_cast")]; |
| tensor<int32, [4]> var_2329 = const()[name = tensor<string, []>("op_2329"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2330_cast = reshape(shape = var_2329, x = tensor_151_cast)[name = tensor<string, []>("op_2330_cast")]; |
| tensor<int32, [4]> var_2331_perm_0 = const()[name = tensor<string, []>("op_2331_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1117155584)))]; |
| 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, []>(1120432448)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_153_cast = 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, x = hidden_states_151_cast)[name = tensor<string, []>("tensor_153_cast")]; |
| tensor<int32, [4]> var_2336 = const()[name = tensor<string, []>("op_2336"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2337_cast = reshape(shape = var_2336, x = tensor_153_cast)[name = tensor<string, []>("op_2337_cast")]; |
| tensor<int32, [4]> var_2338_perm_0 = const()[name = tensor<string, []>("op_2338_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_2345 = const()[name = tensor<string, []>("op_2345"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2346_cast = reshape(shape = var_2345, x = tensor_155_cast)[name = tensor<string, []>("op_2346_cast")]; |
| tensor<int32, [4]> var_2347_perm_0 = const()[name = tensor<string, []>("op_2347_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_2349 = const()[name = tensor<string, []>("op_2349"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_33 = transpose(perm = var_2347_perm_0, x = var_2346_cast)[name = tensor<string, []>("transpose_33")]; |
| tensor<fp16, [20, 77, 64]> query_states_51_cast = reshape(shape = var_2349, x = transpose_33)[name = tensor<string, []>("query_states_51_cast")]; |
| tensor<int32, [3]> var_2351 = const()[name = tensor<string, []>("op_2351"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_35 = transpose(perm = var_2331_perm_0, x = var_2330_cast)[name = tensor<string, []>("transpose_35")]; |
| tensor<fp16, [20, 77, 64]> key_states_103_cast = reshape(shape = var_2351, x = transpose_35)[name = tensor<string, []>("key_states_103_cast")]; |
| tensor<int32, [3]> var_2353 = const()[name = tensor<string, []>("op_2353"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_34 = transpose(perm = var_2338_perm_0, x = var_2337_cast)[name = tensor<string, []>("transpose_34")]; |
| tensor<fp16, [20, 77, 64]> value_states_103_cast = reshape(shape = var_2353, x = transpose_34)[name = tensor<string, []>("value_states_103_cast")]; |
| tensor<int32, [3]> var_2356_perm_0 = const()[name = tensor<string, []>("op_2356_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_151_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_151_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_151_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_151_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_32 = transpose(perm = var_2356_perm_0, x = key_states_103_cast)[name = tensor<string, []>("transpose_32")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_151_cast = matmul(transpose_x = attn_weights_151_transpose_x_0, transpose_y = attn_weights_151_transpose_y_0, x = query_states_51_cast, y = transpose_32)[name = tensor<string, []>("attn_weights_151_cast")]; |
| tensor<int32, [4]> var_2358 = const()[name = tensor<string, []>("op_2358"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_2359_cast = reshape(shape = var_2358, x = attn_weights_151_cast)[name = tensor<string, []>("op_2359_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_153_cast = add(x = var_2359_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_153_cast")]; |
| tensor<int32, [3]> var_2364 = const()[name = tensor<string, []>("op_2364"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_405_cast = reshape(shape = var_2364, x = attn_weights_153_cast)[name = tensor<string, []>("input_405_cast")]; |
| tensor<fp16, [20, 77, 77]> input_407_cast = softmax(axis = var_5, x = input_405_cast)[name = tensor<string, []>("input_407_cast")]; |
| 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 = matmul(transpose_x = attn_output_151_transpose_x_0, transpose_y = attn_output_151_transpose_y_0, x = input_407_cast, y = value_states_103_cast)[name = tensor<string, []>("attn_output_151_cast")]; |
| tensor<int32, [4]> var_2369 = const()[name = tensor<string, []>("op_2369"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_153_cast = reshape(shape = var_2369, x = attn_output_151_cast)[name = tensor<string, []>("attn_output_153_cast")]; |
| 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_2372 = const()[name = tensor<string, []>("op_2372"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_31 = transpose(perm = attn_output_155_perm_0, x = attn_output_153_cast)[name = tensor<string, []>("transpose_31")]; |
| tensor<fp16, [1, 77, 1280]> input_409_cast = reshape(shape = var_2372, x = transpose_31)[name = tensor<string, []>("input_409_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_25_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1120435072)))]; |
| 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, []>(1123711936)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_153_cast = 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, x = input_409_cast)[name = tensor<string, []>("hidden_states_153_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_411_cast = add(x = input_403_cast, y = hidden_states_153_cast)[name = tensor<string, []>("input_411_cast")]; |
| 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, []>(1123714560)))]; |
| 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, []>(1123717184)))]; |
| tensor<fp16, [1, 77, 1280]> input_413_cast = 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)[name = tensor<string, []>("input_413_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_25_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1123719808)))]; |
| 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, []>(1136827072)))]; |
| tensor<fp16, [1, 77, 5120]> input_415_cast = 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, x = input_413_cast)[name = tensor<string, []>("input_415_cast")]; |
| 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 = gelu(mode = input_417_mode_0, x = input_415_cast)[name = tensor<string, []>("input_417_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_25_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1136837376)))]; |
| 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, []>(1149944640)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_155_cast = 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, x = input_417_cast)[name = tensor<string, []>("hidden_states_155_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_419_cast = add(x = input_411_cast, y = hidden_states_155_cast)[name = tensor<string, []>("input_419_cast")]; |
| 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, []>(1149947264)))]; |
| 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, []>(1149949888)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_157_cast = 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)[name = tensor<string, []>("hidden_states_157_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_26_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1149952512)))]; |
| 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, []>(1153229376)))]; |
| tensor<fp16, [1, 77, 1280]> var_2410_cast = 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, x = hidden_states_157_cast)[name = tensor<string, []>("op_2410_cast")]; |
| tensor<fp16, []> var_2411_to_fp16 = const()[name = tensor<string, []>("op_2411_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_161_cast = mul(x = var_2410_cast, y = var_2411_to_fp16)[name = tensor<string, []>("tensor_161_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_26_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1153232000)))]; |
| 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, []>(1156508864)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_157_cast = 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, x = hidden_states_157_cast)[name = tensor<string, []>("tensor_157_cast")]; |
| tensor<int32, [4]> var_2416 = const()[name = tensor<string, []>("op_2416"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2417_cast = reshape(shape = var_2416, x = tensor_157_cast)[name = tensor<string, []>("op_2417_cast")]; |
| tensor<int32, [4]> var_2418_perm_0 = const()[name = tensor<string, []>("op_2418_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1156511488)))]; |
| 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, []>(1159788352)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_159_cast = 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, x = hidden_states_157_cast)[name = tensor<string, []>("tensor_159_cast")]; |
| tensor<int32, [4]> var_2423 = const()[name = tensor<string, []>("op_2423"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2424_cast = reshape(shape = var_2423, x = tensor_159_cast)[name = tensor<string, []>("op_2424_cast")]; |
| tensor<int32, [4]> var_2425_perm_0 = const()[name = tensor<string, []>("op_2425_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_2432 = const()[name = tensor<string, []>("op_2432"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2433_cast = reshape(shape = var_2432, x = tensor_161_cast)[name = tensor<string, []>("op_2433_cast")]; |
| tensor<int32, [4]> var_2434_perm_0 = const()[name = tensor<string, []>("op_2434_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_2436 = const()[name = tensor<string, []>("op_2436"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_28 = transpose(perm = var_2434_perm_0, x = var_2433_cast)[name = tensor<string, []>("transpose_28")]; |
| tensor<fp16, [20, 77, 64]> query_states_53_cast = reshape(shape = var_2436, x = transpose_28)[name = tensor<string, []>("query_states_53_cast")]; |
| tensor<int32, [3]> var_2438 = const()[name = tensor<string, []>("op_2438"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_30 = transpose(perm = var_2418_perm_0, x = var_2417_cast)[name = tensor<string, []>("transpose_30")]; |
| tensor<fp16, [20, 77, 64]> key_states_107_cast = reshape(shape = var_2438, x = transpose_30)[name = tensor<string, []>("key_states_107_cast")]; |
| tensor<int32, [3]> var_2440 = const()[name = tensor<string, []>("op_2440"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_29 = transpose(perm = var_2425_perm_0, x = var_2424_cast)[name = tensor<string, []>("transpose_29")]; |
| tensor<fp16, [20, 77, 64]> value_states_107_cast = reshape(shape = var_2440, x = transpose_29)[name = tensor<string, []>("value_states_107_cast")]; |
| tensor<int32, [3]> var_2443_perm_0 = const()[name = tensor<string, []>("op_2443_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_157_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_157_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_157_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_157_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_27 = transpose(perm = var_2443_perm_0, x = key_states_107_cast)[name = tensor<string, []>("transpose_27")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_157_cast = matmul(transpose_x = attn_weights_157_transpose_x_0, transpose_y = attn_weights_157_transpose_y_0, x = query_states_53_cast, y = transpose_27)[name = tensor<string, []>("attn_weights_157_cast")]; |
| tensor<int32, [4]> var_2445 = const()[name = tensor<string, []>("op_2445"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_2446_cast = reshape(shape = var_2445, x = attn_weights_157_cast)[name = tensor<string, []>("op_2446_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_159_cast = add(x = var_2446_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_159_cast")]; |
| tensor<int32, [3]> var_2451 = const()[name = tensor<string, []>("op_2451"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_421_cast = reshape(shape = var_2451, x = attn_weights_159_cast)[name = tensor<string, []>("input_421_cast")]; |
| tensor<fp16, [20, 77, 77]> input_423_cast = softmax(axis = var_5, x = input_421_cast)[name = tensor<string, []>("input_423_cast")]; |
| 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 = matmul(transpose_x = attn_output_157_transpose_x_0, transpose_y = attn_output_157_transpose_y_0, x = input_423_cast, y = value_states_107_cast)[name = tensor<string, []>("attn_output_157_cast")]; |
| tensor<int32, [4]> var_2456 = const()[name = tensor<string, []>("op_2456"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_159_cast = reshape(shape = var_2456, x = attn_output_157_cast)[name = tensor<string, []>("attn_output_159_cast")]; |
| 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_2459 = const()[name = tensor<string, []>("op_2459"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_26 = transpose(perm = attn_output_161_perm_0, x = attn_output_159_cast)[name = tensor<string, []>("transpose_26")]; |
| tensor<fp16, [1, 77, 1280]> input_425_cast = reshape(shape = var_2459, x = transpose_26)[name = tensor<string, []>("input_425_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_26_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1159790976)))]; |
| 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, []>(1163067840)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_159_cast = 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, x = input_425_cast)[name = tensor<string, []>("hidden_states_159_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_427_cast = add(x = input_419_cast, y = hidden_states_159_cast)[name = tensor<string, []>("input_427_cast")]; |
| 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, []>(1163070464)))]; |
| 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, []>(1163073088)))]; |
| tensor<fp16, [1, 77, 1280]> input_429_cast = 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)[name = tensor<string, []>("input_429_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_26_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1163075712)))]; |
| 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, []>(1176182976)))]; |
| tensor<fp16, [1, 77, 5120]> input_431_cast = 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, x = input_429_cast)[name = tensor<string, []>("input_431_cast")]; |
| 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 = gelu(mode = input_433_mode_0, x = input_431_cast)[name = tensor<string, []>("input_433_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_26_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1176193280)))]; |
| 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, []>(1189300544)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_161_cast = 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, x = input_433_cast)[name = tensor<string, []>("hidden_states_161_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_435_cast = add(x = input_427_cast, y = hidden_states_161_cast)[name = tensor<string, []>("input_435_cast")]; |
| 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, []>(1189303168)))]; |
| 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, []>(1189305792)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_163_cast = 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)[name = tensor<string, []>("hidden_states_163_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_27_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1189308416)))]; |
| 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, []>(1192585280)))]; |
| tensor<fp16, [1, 77, 1280]> var_2497_cast = 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, x = hidden_states_163_cast)[name = tensor<string, []>("op_2497_cast")]; |
| tensor<fp16, []> var_2498_to_fp16 = const()[name = tensor<string, []>("op_2498_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_167_cast = mul(x = var_2497_cast, y = var_2498_to_fp16)[name = tensor<string, []>("tensor_167_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_27_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1192587904)))]; |
| 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, []>(1195864768)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_163_cast = 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, x = hidden_states_163_cast)[name = tensor<string, []>("tensor_163_cast")]; |
| tensor<int32, [4]> var_2503 = const()[name = tensor<string, []>("op_2503"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2504_cast = reshape(shape = var_2503, x = tensor_163_cast)[name = tensor<string, []>("op_2504_cast")]; |
| tensor<int32, [4]> var_2505_perm_0 = const()[name = tensor<string, []>("op_2505_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1195867392)))]; |
| 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, []>(1199144256)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_165_cast = 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, x = hidden_states_163_cast)[name = tensor<string, []>("tensor_165_cast")]; |
| tensor<int32, [4]> var_2510 = const()[name = tensor<string, []>("op_2510"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2511_cast = reshape(shape = var_2510, x = tensor_165_cast)[name = tensor<string, []>("op_2511_cast")]; |
| tensor<int32, [4]> var_2512_perm_0 = const()[name = tensor<string, []>("op_2512_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_2519 = const()[name = tensor<string, []>("op_2519"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2520_cast = reshape(shape = var_2519, x = tensor_167_cast)[name = tensor<string, []>("op_2520_cast")]; |
| tensor<int32, [4]> var_2521_perm_0 = const()[name = tensor<string, []>("op_2521_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_2523 = const()[name = tensor<string, []>("op_2523"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_23 = transpose(perm = var_2521_perm_0, x = var_2520_cast)[name = tensor<string, []>("transpose_23")]; |
| tensor<fp16, [20, 77, 64]> query_states_55_cast = reshape(shape = var_2523, x = transpose_23)[name = tensor<string, []>("query_states_55_cast")]; |
| tensor<int32, [3]> var_2525 = const()[name = tensor<string, []>("op_2525"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_25 = transpose(perm = var_2505_perm_0, x = var_2504_cast)[name = tensor<string, []>("transpose_25")]; |
| tensor<fp16, [20, 77, 64]> key_states_111_cast = reshape(shape = var_2525, x = transpose_25)[name = tensor<string, []>("key_states_111_cast")]; |
| tensor<int32, [3]> var_2527 = const()[name = tensor<string, []>("op_2527"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_24 = transpose(perm = var_2512_perm_0, x = var_2511_cast)[name = tensor<string, []>("transpose_24")]; |
| tensor<fp16, [20, 77, 64]> value_states_111_cast = reshape(shape = var_2527, x = transpose_24)[name = tensor<string, []>("value_states_111_cast")]; |
| tensor<int32, [3]> var_2530_perm_0 = const()[name = tensor<string, []>("op_2530_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_163_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_163_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_163_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_163_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_22 = transpose(perm = var_2530_perm_0, x = key_states_111_cast)[name = tensor<string, []>("transpose_22")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_163_cast = matmul(transpose_x = attn_weights_163_transpose_x_0, transpose_y = attn_weights_163_transpose_y_0, x = query_states_55_cast, y = transpose_22)[name = tensor<string, []>("attn_weights_163_cast")]; |
| tensor<int32, [4]> var_2532 = const()[name = tensor<string, []>("op_2532"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_2533_cast = reshape(shape = var_2532, x = attn_weights_163_cast)[name = tensor<string, []>("op_2533_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_165_cast = add(x = var_2533_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_165_cast")]; |
| tensor<int32, [3]> var_2538 = const()[name = tensor<string, []>("op_2538"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_437_cast = reshape(shape = var_2538, x = attn_weights_165_cast)[name = tensor<string, []>("input_437_cast")]; |
| tensor<fp16, [20, 77, 77]> input_439_cast = softmax(axis = var_5, x = input_437_cast)[name = tensor<string, []>("input_439_cast")]; |
| 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 = matmul(transpose_x = attn_output_163_transpose_x_0, transpose_y = attn_output_163_transpose_y_0, x = input_439_cast, y = value_states_111_cast)[name = tensor<string, []>("attn_output_163_cast")]; |
| tensor<int32, [4]> var_2543 = const()[name = tensor<string, []>("op_2543"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_165_cast = reshape(shape = var_2543, x = attn_output_163_cast)[name = tensor<string, []>("attn_output_165_cast")]; |
| 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_2546 = const()[name = tensor<string, []>("op_2546"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_21 = transpose(perm = attn_output_167_perm_0, x = attn_output_165_cast)[name = tensor<string, []>("transpose_21")]; |
| tensor<fp16, [1, 77, 1280]> input_441_cast = reshape(shape = var_2546, x = transpose_21)[name = tensor<string, []>("input_441_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_27_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1199146880)))]; |
| 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, []>(1202423744)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_165_cast = 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, x = input_441_cast)[name = tensor<string, []>("hidden_states_165_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_443_cast = add(x = input_435_cast, y = hidden_states_165_cast)[name = tensor<string, []>("input_443_cast")]; |
| 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, []>(1202426368)))]; |
| 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, []>(1202428992)))]; |
| tensor<fp16, [1, 77, 1280]> input_445_cast = 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)[name = tensor<string, []>("input_445_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_27_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1202431616)))]; |
| 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, []>(1215538880)))]; |
| tensor<fp16, [1, 77, 5120]> input_447_cast = 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, x = input_445_cast)[name = tensor<string, []>("input_447_cast")]; |
| 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 = gelu(mode = input_449_mode_0, x = input_447_cast)[name = tensor<string, []>("input_449_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_27_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1215549184)))]; |
| 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, []>(1228656448)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_167_cast = 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, x = input_449_cast)[name = tensor<string, []>("hidden_states_167_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_451_cast = add(x = input_443_cast, y = hidden_states_167_cast)[name = tensor<string, []>("input_451_cast")]; |
| 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, []>(1228659072)))]; |
| 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, []>(1228661696)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_169_cast = 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)[name = tensor<string, []>("hidden_states_169_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_28_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1228664320)))]; |
| 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, []>(1231941184)))]; |
| tensor<fp16, [1, 77, 1280]> var_2584_cast = 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, x = hidden_states_169_cast)[name = tensor<string, []>("op_2584_cast")]; |
| tensor<fp16, []> var_2585_to_fp16 = const()[name = tensor<string, []>("op_2585_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_173_cast = mul(x = var_2584_cast, y = var_2585_to_fp16)[name = tensor<string, []>("tensor_173_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_28_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1231943808)))]; |
| 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, []>(1235220672)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_169_cast = 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, x = hidden_states_169_cast)[name = tensor<string, []>("tensor_169_cast")]; |
| tensor<int32, [4]> var_2590 = const()[name = tensor<string, []>("op_2590"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2591_cast = reshape(shape = var_2590, x = tensor_169_cast)[name = tensor<string, []>("op_2591_cast")]; |
| tensor<int32, [4]> var_2592_perm_0 = const()[name = tensor<string, []>("op_2592_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1235223296)))]; |
| 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, []>(1238500160)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_171_cast = 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, x = hidden_states_169_cast)[name = tensor<string, []>("tensor_171_cast")]; |
| tensor<int32, [4]> var_2597 = const()[name = tensor<string, []>("op_2597"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2598_cast = reshape(shape = var_2597, x = tensor_171_cast)[name = tensor<string, []>("op_2598_cast")]; |
| tensor<int32, [4]> var_2599_perm_0 = const()[name = tensor<string, []>("op_2599_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_2606 = const()[name = tensor<string, []>("op_2606"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2607_cast = reshape(shape = var_2606, x = tensor_173_cast)[name = tensor<string, []>("op_2607_cast")]; |
| tensor<int32, [4]> var_2608_perm_0 = const()[name = tensor<string, []>("op_2608_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_2610 = const()[name = tensor<string, []>("op_2610"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_18 = transpose(perm = var_2608_perm_0, x = var_2607_cast)[name = tensor<string, []>("transpose_18")]; |
| tensor<fp16, [20, 77, 64]> query_states_57_cast = reshape(shape = var_2610, x = transpose_18)[name = tensor<string, []>("query_states_57_cast")]; |
| tensor<int32, [3]> var_2612 = const()[name = tensor<string, []>("op_2612"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_20 = transpose(perm = var_2592_perm_0, x = var_2591_cast)[name = tensor<string, []>("transpose_20")]; |
| tensor<fp16, [20, 77, 64]> key_states_115_cast = reshape(shape = var_2612, x = transpose_20)[name = tensor<string, []>("key_states_115_cast")]; |
| tensor<int32, [3]> var_2614 = const()[name = tensor<string, []>("op_2614"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_19 = transpose(perm = var_2599_perm_0, x = var_2598_cast)[name = tensor<string, []>("transpose_19")]; |
| tensor<fp16, [20, 77, 64]> value_states_115_cast = reshape(shape = var_2614, x = transpose_19)[name = tensor<string, []>("value_states_115_cast")]; |
| tensor<int32, [3]> var_2617_perm_0 = const()[name = tensor<string, []>("op_2617_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_169_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_169_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_169_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_169_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_17 = transpose(perm = var_2617_perm_0, x = key_states_115_cast)[name = tensor<string, []>("transpose_17")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_169_cast = matmul(transpose_x = attn_weights_169_transpose_x_0, transpose_y = attn_weights_169_transpose_y_0, x = query_states_57_cast, y = transpose_17)[name = tensor<string, []>("attn_weights_169_cast")]; |
| tensor<int32, [4]> var_2619 = const()[name = tensor<string, []>("op_2619"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_2620_cast = reshape(shape = var_2619, x = attn_weights_169_cast)[name = tensor<string, []>("op_2620_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_171_cast = add(x = var_2620_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_171_cast")]; |
| tensor<int32, [3]> var_2625 = const()[name = tensor<string, []>("op_2625"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_453_cast = reshape(shape = var_2625, x = attn_weights_171_cast)[name = tensor<string, []>("input_453_cast")]; |
| tensor<fp16, [20, 77, 77]> input_455_cast = softmax(axis = var_5, x = input_453_cast)[name = tensor<string, []>("input_455_cast")]; |
| 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 = matmul(transpose_x = attn_output_169_transpose_x_0, transpose_y = attn_output_169_transpose_y_0, x = input_455_cast, y = value_states_115_cast)[name = tensor<string, []>("attn_output_169_cast")]; |
| tensor<int32, [4]> var_2630 = const()[name = tensor<string, []>("op_2630"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_171_cast = reshape(shape = var_2630, x = attn_output_169_cast)[name = tensor<string, []>("attn_output_171_cast")]; |
| 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_2633 = const()[name = tensor<string, []>("op_2633"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_16 = transpose(perm = attn_output_173_perm_0, x = attn_output_171_cast)[name = tensor<string, []>("transpose_16")]; |
| tensor<fp16, [1, 77, 1280]> input_457_cast = reshape(shape = var_2633, x = transpose_16)[name = tensor<string, []>("input_457_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_28_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1238502784)))]; |
| 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, []>(1241779648)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_171_cast = 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, x = input_457_cast)[name = tensor<string, []>("hidden_states_171_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_459_cast = add(x = input_451_cast, y = hidden_states_171_cast)[name = tensor<string, []>("input_459_cast")]; |
| 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, []>(1241782272)))]; |
| 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, []>(1241784896)))]; |
| tensor<fp16, [1, 77, 1280]> input_461_cast = 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)[name = tensor<string, []>("input_461_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_28_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1241787520)))]; |
| 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, []>(1254894784)))]; |
| tensor<fp16, [1, 77, 5120]> input_463_cast = 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, x = input_461_cast)[name = tensor<string, []>("input_463_cast")]; |
| 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 = gelu(mode = input_465_mode_0, x = input_463_cast)[name = tensor<string, []>("input_465_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_28_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1254905088)))]; |
| 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, []>(1268012352)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_173_cast = 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, x = input_465_cast)[name = tensor<string, []>("hidden_states_173_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_467_cast = add(x = input_459_cast, y = hidden_states_173_cast)[name = tensor<string, []>("input_467_cast")]; |
| 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, []>(1268014976)))]; |
| 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, []>(1268017600)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_175_cast = 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)[name = tensor<string, []>("hidden_states_175_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_29_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1268020224)))]; |
| 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, []>(1271297088)))]; |
| tensor<fp16, [1, 77, 1280]> var_2671_cast = 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, x = hidden_states_175_cast)[name = tensor<string, []>("op_2671_cast")]; |
| tensor<fp16, []> var_2672_to_fp16 = const()[name = tensor<string, []>("op_2672_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_179_cast = mul(x = var_2671_cast, y = var_2672_to_fp16)[name = tensor<string, []>("tensor_179_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_29_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1271299712)))]; |
| 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, []>(1274576576)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_175_cast = 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, x = hidden_states_175_cast)[name = tensor<string, []>("tensor_175_cast")]; |
| tensor<int32, [4]> var_2677 = const()[name = tensor<string, []>("op_2677"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2678_cast = reshape(shape = var_2677, x = tensor_175_cast)[name = tensor<string, []>("op_2678_cast")]; |
| tensor<int32, [4]> var_2679_perm_0 = const()[name = tensor<string, []>("op_2679_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1274579200)))]; |
| 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, []>(1277856064)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_177_cast = 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, x = hidden_states_175_cast)[name = tensor<string, []>("tensor_177_cast")]; |
| tensor<int32, [4]> var_2684 = const()[name = tensor<string, []>("op_2684"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2685_cast = reshape(shape = var_2684, x = tensor_177_cast)[name = tensor<string, []>("op_2685_cast")]; |
| tensor<int32, [4]> var_2686_perm_0 = const()[name = tensor<string, []>("op_2686_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_2693 = const()[name = tensor<string, []>("op_2693"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2694_cast = reshape(shape = var_2693, x = tensor_179_cast)[name = tensor<string, []>("op_2694_cast")]; |
| tensor<int32, [4]> var_2695_perm_0 = const()[name = tensor<string, []>("op_2695_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_2697 = const()[name = tensor<string, []>("op_2697"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_13 = transpose(perm = var_2695_perm_0, x = var_2694_cast)[name = tensor<string, []>("transpose_13")]; |
| tensor<fp16, [20, 77, 64]> query_states_59_cast = reshape(shape = var_2697, x = transpose_13)[name = tensor<string, []>("query_states_59_cast")]; |
| tensor<int32, [3]> var_2699 = const()[name = tensor<string, []>("op_2699"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_15 = transpose(perm = var_2679_perm_0, x = var_2678_cast)[name = tensor<string, []>("transpose_15")]; |
| tensor<fp16, [20, 77, 64]> key_states_119_cast = reshape(shape = var_2699, x = transpose_15)[name = tensor<string, []>("key_states_119_cast")]; |
| tensor<int32, [3]> var_2701 = const()[name = tensor<string, []>("op_2701"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_14 = transpose(perm = var_2686_perm_0, x = var_2685_cast)[name = tensor<string, []>("transpose_14")]; |
| tensor<fp16, [20, 77, 64]> value_states_119_cast = reshape(shape = var_2701, x = transpose_14)[name = tensor<string, []>("value_states_119_cast")]; |
| tensor<int32, [3]> var_2704_perm_0 = const()[name = tensor<string, []>("op_2704_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_175_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_175_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_175_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_175_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_12 = transpose(perm = var_2704_perm_0, x = key_states_119_cast)[name = tensor<string, []>("transpose_12")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_175_cast = matmul(transpose_x = attn_weights_175_transpose_x_0, transpose_y = attn_weights_175_transpose_y_0, x = query_states_59_cast, y = transpose_12)[name = tensor<string, []>("attn_weights_175_cast")]; |
| tensor<int32, [4]> var_2706 = const()[name = tensor<string, []>("op_2706"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_2707_cast = reshape(shape = var_2706, x = attn_weights_175_cast)[name = tensor<string, []>("op_2707_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_177_cast = add(x = var_2707_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_177_cast")]; |
| tensor<int32, [3]> var_2712 = const()[name = tensor<string, []>("op_2712"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_469_cast = reshape(shape = var_2712, x = attn_weights_177_cast)[name = tensor<string, []>("input_469_cast")]; |
| tensor<fp16, [20, 77, 77]> input_471_cast = softmax(axis = var_5, x = input_469_cast)[name = tensor<string, []>("input_471_cast")]; |
| 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 = matmul(transpose_x = attn_output_175_transpose_x_0, transpose_y = attn_output_175_transpose_y_0, x = input_471_cast, y = value_states_119_cast)[name = tensor<string, []>("attn_output_175_cast")]; |
| tensor<int32, [4]> var_2717 = const()[name = tensor<string, []>("op_2717"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_177_cast = reshape(shape = var_2717, x = attn_output_175_cast)[name = tensor<string, []>("attn_output_177_cast")]; |
| 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_2720 = const()[name = tensor<string, []>("op_2720"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_11 = transpose(perm = attn_output_179_perm_0, x = attn_output_177_cast)[name = tensor<string, []>("transpose_11")]; |
| tensor<fp16, [1, 77, 1280]> input_473_cast = reshape(shape = var_2720, x = transpose_11)[name = tensor<string, []>("input_473_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_29_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1277858688)))]; |
| 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, []>(1281135552)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_177_cast = 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, x = input_473_cast)[name = tensor<string, []>("hidden_states_177_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_475_cast = add(x = input_467_cast, y = hidden_states_177_cast)[name = tensor<string, []>("input_475_cast")]; |
| 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, []>(1281138176)))]; |
| 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, []>(1281140800)))]; |
| tensor<fp16, [1, 77, 1280]> input_477_cast = 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)[name = tensor<string, []>("input_477_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_29_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1281143424)))]; |
| 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, []>(1294250688)))]; |
| tensor<fp16, [1, 77, 5120]> input_479_cast = 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, x = input_477_cast)[name = tensor<string, []>("input_479_cast")]; |
| 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 = gelu(mode = input_481_mode_0, x = input_479_cast)[name = tensor<string, []>("input_481_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_29_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1294260992)))]; |
| 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, []>(1307368256)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_179_cast = 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, x = input_481_cast)[name = tensor<string, []>("hidden_states_179_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_483_cast = add(x = input_475_cast, y = hidden_states_179_cast)[name = tensor<string, []>("input_483_cast")]; |
| 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, []>(1307370880)))]; |
| 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, []>(1307373504)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_181_cast = 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)[name = tensor<string, []>("hidden_states_181_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_30_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1307376128)))]; |
| 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, []>(1310652992)))]; |
| tensor<fp16, [1, 77, 1280]> var_2758_cast = 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, x = hidden_states_181_cast)[name = tensor<string, []>("op_2758_cast")]; |
| tensor<fp16, []> var_2759_to_fp16 = const()[name = tensor<string, []>("op_2759_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_185_cast = mul(x = var_2758_cast, y = var_2759_to_fp16)[name = tensor<string, []>("tensor_185_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_30_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1310655616)))]; |
| 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, []>(1313932480)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_181_cast = 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, x = hidden_states_181_cast)[name = tensor<string, []>("tensor_181_cast")]; |
| tensor<int32, [4]> var_2764 = const()[name = tensor<string, []>("op_2764"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2765_cast = reshape(shape = var_2764, x = tensor_181_cast)[name = tensor<string, []>("op_2765_cast")]; |
| tensor<int32, [4]> var_2766_perm_0 = const()[name = tensor<string, []>("op_2766_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1313935104)))]; |
| 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, []>(1317211968)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_183_cast = 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, x = hidden_states_181_cast)[name = tensor<string, []>("tensor_183_cast")]; |
| tensor<int32, [4]> var_2771 = const()[name = tensor<string, []>("op_2771"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2772_cast = reshape(shape = var_2771, x = tensor_183_cast)[name = tensor<string, []>("op_2772_cast")]; |
| tensor<int32, [4]> var_2773_perm_0 = const()[name = tensor<string, []>("op_2773_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_2780 = const()[name = tensor<string, []>("op_2780"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2781_cast = reshape(shape = var_2780, x = tensor_185_cast)[name = tensor<string, []>("op_2781_cast")]; |
| tensor<int32, [4]> var_2782_perm_0 = const()[name = tensor<string, []>("op_2782_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_2784 = const()[name = tensor<string, []>("op_2784"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_8 = transpose(perm = var_2782_perm_0, x = var_2781_cast)[name = tensor<string, []>("transpose_8")]; |
| tensor<fp16, [20, 77, 64]> query_states_61_cast = reshape(shape = var_2784, x = transpose_8)[name = tensor<string, []>("query_states_61_cast")]; |
| tensor<int32, [3]> var_2786 = const()[name = tensor<string, []>("op_2786"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_10 = transpose(perm = var_2766_perm_0, x = var_2765_cast)[name = tensor<string, []>("transpose_10")]; |
| tensor<fp16, [20, 77, 64]> key_states_123_cast = reshape(shape = var_2786, x = transpose_10)[name = tensor<string, []>("key_states_123_cast")]; |
| tensor<int32, [3]> var_2788 = const()[name = tensor<string, []>("op_2788"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_9 = transpose(perm = var_2773_perm_0, x = var_2772_cast)[name = tensor<string, []>("transpose_9")]; |
| tensor<fp16, [20, 77, 64]> value_states_123_cast = reshape(shape = var_2788, x = transpose_9)[name = tensor<string, []>("value_states_123_cast")]; |
| tensor<int32, [3]> var_2791_perm_0 = const()[name = tensor<string, []>("op_2791_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_181_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_181_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_181_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_181_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_7 = transpose(perm = var_2791_perm_0, x = key_states_123_cast)[name = tensor<string, []>("transpose_7")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_181_cast = matmul(transpose_x = attn_weights_181_transpose_x_0, transpose_y = attn_weights_181_transpose_y_0, x = query_states_61_cast, y = transpose_7)[name = tensor<string, []>("attn_weights_181_cast")]; |
| tensor<int32, [4]> var_2793 = const()[name = tensor<string, []>("op_2793"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_2794_cast = reshape(shape = var_2793, x = attn_weights_181_cast)[name = tensor<string, []>("op_2794_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_183_cast = add(x = var_2794_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_183_cast")]; |
| tensor<int32, [3]> var_2799 = const()[name = tensor<string, []>("op_2799"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_485_cast = reshape(shape = var_2799, x = attn_weights_183_cast)[name = tensor<string, []>("input_485_cast")]; |
| tensor<fp16, [20, 77, 77]> input_487_cast = softmax(axis = var_5, x = input_485_cast)[name = tensor<string, []>("input_487_cast")]; |
| 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 = matmul(transpose_x = attn_output_181_transpose_x_0, transpose_y = attn_output_181_transpose_y_0, x = input_487_cast, y = value_states_123_cast)[name = tensor<string, []>("attn_output_181_cast")]; |
| tensor<int32, [4]> var_2804 = const()[name = tensor<string, []>("op_2804"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_183_cast = reshape(shape = var_2804, x = attn_output_181_cast)[name = tensor<string, []>("attn_output_183_cast")]; |
| 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_2807 = const()[name = tensor<string, []>("op_2807"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_6 = transpose(perm = attn_output_185_perm_0, x = attn_output_183_cast)[name = tensor<string, []>("transpose_6")]; |
| tensor<fp16, [1, 77, 1280]> input_489_cast = reshape(shape = var_2807, x = transpose_6)[name = tensor<string, []>("input_489_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_30_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1317214592)))]; |
| 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, []>(1320491456)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_183_cast = 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, x = input_489_cast)[name = tensor<string, []>("hidden_states_183_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_491_cast = add(x = input_483_cast, y = hidden_states_183_cast)[name = tensor<string, []>("input_491_cast")]; |
| 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, []>(1320494080)))]; |
| 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, []>(1320496704)))]; |
| tensor<fp16, [1, 77, 1280]> input_493_cast = 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)[name = tensor<string, []>("input_493_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_30_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1320499328)))]; |
| 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, []>(1333606592)))]; |
| tensor<fp16, [1, 77, 5120]> input_495_cast = 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, x = input_493_cast)[name = tensor<string, []>("input_495_cast")]; |
| 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 = gelu(mode = input_497_mode_0, x = input_495_cast)[name = tensor<string, []>("input_497_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_30_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1333616896)))]; |
| 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, []>(1346724160)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_185_cast = 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, x = input_497_cast)[name = tensor<string, []>("hidden_states_185_cast")]; |
| tensor<fp16, [1, 77, 1280]> hidden_embeds = add(x = input_491_cast, y = hidden_states_185_cast)[name = tensor<string, []>("input_499_cast")]; |
| 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, []>(1346726784)))]; |
| 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, []>(1346729408)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_187_cast = 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 = hidden_embeds)[name = tensor<string, []>("hidden_states_187_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_31_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1346732032)))]; |
| 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, []>(1350008896)))]; |
| tensor<fp16, [1, 77, 1280]> var_2845_cast = 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, x = hidden_states_187_cast)[name = tensor<string, []>("op_2845_cast")]; |
| tensor<fp16, []> var_2846_to_fp16 = const()[name = tensor<string, []>("op_2846_to_fp16"), val = tensor<fp16, []>(0x1p-3)]; |
| tensor<fp16, [1, 77, 1280]> tensor_cast = mul(x = var_2845_cast, y = var_2846_to_fp16)[name = tensor<string, []>("tensor_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_31_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1350011520)))]; |
| 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, []>(1353288384)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_187_cast = 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, x = hidden_states_187_cast)[name = tensor<string, []>("tensor_187_cast")]; |
| tensor<int32, [4]> var_2851 = const()[name = tensor<string, []>("op_2851"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2852_cast = reshape(shape = var_2851, x = tensor_187_cast)[name = tensor<string, []>("op_2852_cast")]; |
| tensor<int32, [4]> var_2853_perm_0 = const()[name = tensor<string, []>("op_2853_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 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1353291008)))]; |
| 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, []>(1356567872)))]; |
| tensor<fp16, [1, 77, 1280]> tensor_189_cast = 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, x = hidden_states_187_cast)[name = tensor<string, []>("tensor_189_cast")]; |
| tensor<int32, [4]> var_2858 = const()[name = tensor<string, []>("op_2858"), val = tensor<int32, [4]>([1, -1, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2859_cast = reshape(shape = var_2858, x = tensor_189_cast)[name = tensor<string, []>("op_2859_cast")]; |
| tensor<int32, [4]> var_2860_perm_0 = const()[name = tensor<string, []>("op_2860_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [4]> var_2867 = const()[name = tensor<string, []>("op_2867"), val = tensor<int32, [4]>([1, 77, 20, 64])]; |
| tensor<fp16, [1, 77, 20, 64]> var_2868_cast = reshape(shape = var_2867, x = tensor_cast)[name = tensor<string, []>("op_2868_cast")]; |
| tensor<int32, [4]> var_2869_perm_0 = const()[name = tensor<string, []>("op_2869_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_2871 = const()[name = tensor<string, []>("op_2871"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_3 = transpose(perm = var_2869_perm_0, x = var_2868_cast)[name = tensor<string, []>("transpose_3")]; |
| tensor<fp16, [20, 77, 64]> query_states_cast = reshape(shape = var_2871, x = transpose_3)[name = tensor<string, []>("query_states_cast")]; |
| tensor<int32, [3]> var_2873 = const()[name = tensor<string, []>("op_2873"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_5 = transpose(perm = var_2853_perm_0, x = var_2852_cast)[name = tensor<string, []>("transpose_5")]; |
| tensor<fp16, [20, 77, 64]> key_states_cast = reshape(shape = var_2873, x = transpose_5)[name = tensor<string, []>("key_states_cast")]; |
| tensor<int32, [3]> var_2875 = const()[name = tensor<string, []>("op_2875"), val = tensor<int32, [3]>([20, -1, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> transpose_4 = transpose(perm = var_2860_perm_0, x = var_2859_cast)[name = tensor<string, []>("transpose_4")]; |
| tensor<fp16, [20, 77, 64]> value_states_cast = reshape(shape = var_2875, x = transpose_4)[name = tensor<string, []>("value_states_cast")]; |
| tensor<int32, [3]> var_2878_perm_0 = const()[name = tensor<string, []>("op_2878_perm_0"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<bool, []> attn_weights_187_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_187_transpose_x_0"), val = tensor<bool, []>(false)]; |
| tensor<bool, []> attn_weights_187_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_187_transpose_y_0"), val = tensor<bool, []>(false)]; |
| tensor<fp16, [20, 64, 77]> transpose_2 = transpose(perm = var_2878_perm_0, x = key_states_cast)[name = tensor<string, []>("transpose_2")]; |
| tensor<fp16, [20, 77, 77]> attn_weights_187_cast = matmul(transpose_x = attn_weights_187_transpose_x_0, transpose_y = attn_weights_187_transpose_y_0, x = query_states_cast, y = transpose_2)[name = tensor<string, []>("attn_weights_187_cast")]; |
| tensor<int32, [4]> var_2880 = const()[name = tensor<string, []>("op_2880"), val = tensor<int32, [4]>([1, 20, 77, 77])]; |
| tensor<fp16, [1, 20, 77, 77]> var_2881_cast = reshape(shape = var_2880, x = attn_weights_187_cast)[name = tensor<string, []>("op_2881_cast")]; |
| tensor<fp16, [1, 20, 77, 77]> attn_weights_189_cast = add(x = var_2881_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_189_cast")]; |
| tensor<int32, [3]> var_2886 = const()[name = tensor<string, []>("op_2886"), val = tensor<int32, [3]>([20, 77, 77])]; |
| tensor<fp16, [20, 77, 77]> input_501_cast = reshape(shape = var_2886, x = attn_weights_189_cast)[name = tensor<string, []>("input_501_cast")]; |
| tensor<fp16, [20, 77, 77]> input_503_cast = softmax(axis = var_5, x = input_501_cast)[name = tensor<string, []>("input_503_cast")]; |
| 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 = matmul(transpose_x = attn_output_187_transpose_x_0, transpose_y = attn_output_187_transpose_y_0, x = input_503_cast, y = value_states_cast)[name = tensor<string, []>("attn_output_187_cast")]; |
| tensor<int32, [4]> var_2891 = const()[name = tensor<string, []>("op_2891"), val = tensor<int32, [4]>([1, 20, 77, 64])]; |
| tensor<fp16, [1, 20, 77, 64]> attn_output_189_cast = reshape(shape = var_2891, x = attn_output_187_cast)[name = tensor<string, []>("attn_output_189_cast")]; |
| 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_2894 = const()[name = tensor<string, []>("op_2894"), val = tensor<int32, [3]>([1, 77, 1280])]; |
| tensor<fp16, [1, 77, 20, 64]> transpose_1 = transpose(perm = attn_output_perm_0, x = attn_output_189_cast)[name = tensor<string, []>("transpose_1")]; |
| tensor<fp16, [1, 77, 1280]> input_505_cast = reshape(shape = var_2894, x = transpose_1)[name = tensor<string, []>("input_505_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_31_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1356570496)))]; |
| 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, []>(1359847360)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_189_cast = 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, x = input_505_cast)[name = tensor<string, []>("hidden_states_189_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_507_cast = add(x = hidden_embeds, y = hidden_states_189_cast)[name = tensor<string, []>("input_507_cast")]; |
| 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, []>(1359849984)))]; |
| 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, []>(1359852608)))]; |
| tensor<fp16, [1, 77, 1280]> input_509_cast = 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)[name = tensor<string, []>("input_509_cast")]; |
| tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_31_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1359855232)))]; |
| 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, []>(1372962496)))]; |
| tensor<fp16, [1, 77, 5120]> input_511_cast = 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, x = input_509_cast)[name = tensor<string, []>("input_511_cast")]; |
| 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 = gelu(mode = input_513_mode_0, x = input_511_cast)[name = tensor<string, []>("input_513_cast")]; |
| tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_31_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1372972800)))]; |
| 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, []>(1386080064)))]; |
| tensor<fp16, [1, 77, 1280]> hidden_states_cast = 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, x = input_513_cast)[name = tensor<string, []>("hidden_states_cast")]; |
| tensor<fp16, [1, 77, 1280]> input_515_cast = add(x = input_507_cast, y = hidden_states_cast)[name = tensor<string, []>("input_515_cast")]; |
| 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, []>(1386082688)))]; |
| 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, []>(1386085312)))]; |
| tensor<fp16, [1, 77, 1280]> last_hidden_state_cast = 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)[name = tensor<string, []>("last_hidden_state_cast")]; |
| tensor<int32, [1]> var_2922 = const()[name = tensor<string, []>("op_2922"), val = tensor<int32, [1]>([0])]; |
| tensor<int32, [1]> var_2924 = reduce_argmax(axis = var_5, keep_dims = var_6, x = cast_1326)[name = tensor<string, []>("op_2924")]; |
| 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_2922, var_2924))[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 = gather_nd(batch_dims = input_transpose_batch_dims_0, indices = stack_0, x = last_hidden_state_cast)[name = tensor<string, []>("input_transpose_cast")]; |
| tensor<fp16, [1280, 1280]> text_encoder_text_projection_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_projection_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1386087936)))]; |
| tensor<fp16, [1280]> var_2931_bias_0_to_fp16 = const()[name = tensor<string, []>("op_2931_bias_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1389364800)))]; |
| tensor<fp16, [1, 1280]> pooled_outputs = linear(bias = var_2931_bias_0_to_fp16, weight = text_encoder_text_projection_weight_to_fp16, x = input_transpose_cast)[name = tensor<string, []>("op_2931_cast")]; |
| } -> (hidden_embeds, pooled_outputs); |
| } |
