program(1.0) [buildInfo = dict, tensor>({{"coremlc-component-MIL", "3510.2.1"}, {"coremlc-version", "3500.32.1"}, {"coremltools-component-torch", "2.9.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "9.0"}})] { func main(tensor audio) [FlexibleShapeInformation = tuple, dict, tensor>>, tuple, dict, list, ?>>>>((("DefaultShapes", {{"audio", [1, 1, 1920]}}), ("RangeDims", {{"audio", [[1, 1], [1, 1], [1920, 1440000]]}})))] { tensor speaker_proj_weight = const()[name = tensor("speaker_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; tensor encoder_model_0_conv_bias = const()[name = tensor("encoder_model_0_conv_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2097280)))]; tensor encoder_model_0_conv_weight = const()[name = tensor("encoder_model_0_conv_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2097600)))]; tensor encoder_model_1_block_1_conv_bias = const()[name = tensor("encoder_model_1_block_1_conv_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2099456)))]; tensor encoder_model_1_block_1_conv_weight = const()[name = tensor("encoder_model_1_block_1_conv_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2099648)))]; tensor encoder_model_1_block_3_conv_bias = const()[name = tensor("encoder_model_1_block_3_conv_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2124288)))]; tensor encoder_model_1_block_3_conv_weight = const()[name = tensor("encoder_model_1_block_3_conv_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2124608)))]; tensor encoder_model_3_conv_bias = const()[name = tensor("encoder_model_3_conv_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2132864)))]; tensor encoder_model_3_conv_weight = const()[name = tensor("encoder_model_3_conv_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2133440)))]; tensor encoder_model_4_block_1_conv_bias = const()[name = tensor("encoder_model_4_block_1_conv_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2395648)))]; tensor encoder_model_4_block_1_conv_weight = const()[name = tensor("encoder_model_4_block_1_conv_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2395968)))]; tensor encoder_model_4_block_3_conv_bias = const()[name = tensor("encoder_model_4_block_3_conv_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2494336)))]; tensor encoder_model_4_block_3_conv_weight = const()[name = tensor("encoder_model_4_block_3_conv_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2494912)))]; tensor encoder_model_6_conv_bias = const()[name = tensor("encoder_model_6_conv_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2527744)))]; tensor encoder_model_6_conv_weight = const()[name = tensor("encoder_model_6_conv_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2528832)))]; tensor encoder_model_7_block_1_conv_bias = const()[name = tensor("encoder_model_7_block_1_conv_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3839616)))]; tensor encoder_model_7_block_1_conv_weight = const()[name = tensor("encoder_model_7_block_1_conv_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3840192)))]; tensor encoder_model_7_block_3_conv_bias = const()[name = tensor("encoder_model_7_block_3_conv_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4233472)))]; tensor encoder_model_7_block_3_conv_weight = const()[name = tensor("encoder_model_7_block_3_conv_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4234560)))]; tensor encoder_model_9_conv_bias = const()[name = tensor("encoder_model_9_conv_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4365696)))]; tensor encoder_model_9_conv_weight = const()[name = tensor("encoder_model_9_conv_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4367808)))]; tensor encoder_model_11_conv_bias = const()[name = tensor("encoder_model_11_conv_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10659328)))]; tensor encoder_model_11_conv_weight = const()[name = tensor("encoder_model_11_conv_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10661440)))]; tensor encoder_transformer_transformer_layers_0_norm1_bias = const()[name = tensor("encoder_transformer_transformer_layers_0_norm1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13807232)))]; tensor encoder_transformer_transformer_layers_0_norm1_weight = const()[name = tensor("encoder_transformer_transformer_layers_0_norm1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13809344)))]; tensor encoder_transformer_transformer_layers_0_self_attn_in_proj_weight = const()[name = tensor("encoder_transformer_transformer_layers_0_self_attn_in_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13811456)))]; tensor encoder_transformer_transformer_layers_0_self_attn_out_proj_weight = const()[name = tensor("encoder_transformer_transformer_layers_0_self_attn_out_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(16957248)))]; tensor encoder_transformer_transformer_layers_0_layer_scale_1_scale = const()[name = tensor("encoder_transformer_transformer_layers_0_layer_scale_1_scale"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18005888)))]; tensor encoder_transformer_transformer_layers_0_norm2_bias = const()[name = tensor("encoder_transformer_transformer_layers_0_norm2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18008000)))]; tensor encoder_transformer_transformer_layers_0_norm2_weight = const()[name = tensor("encoder_transformer_transformer_layers_0_norm2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18010112)))]; tensor encoder_transformer_transformer_layers_0_linear1_weight = const()[name = tensor("encoder_transformer_transformer_layers_0_linear1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18012224)))]; tensor encoder_transformer_transformer_layers_0_linear2_weight = const()[name = tensor("encoder_transformer_transformer_layers_0_linear2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22206592)))]; tensor encoder_transformer_transformer_layers_0_layer_scale_2_scale = const()[name = tensor("encoder_transformer_transformer_layers_0_layer_scale_2_scale"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26400960)))]; tensor encoder_transformer_transformer_layers_1_norm1_bias = const()[name = tensor("encoder_transformer_transformer_layers_1_norm1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26403072)))]; tensor encoder_transformer_transformer_layers_1_norm1_weight = const()[name = tensor("encoder_transformer_transformer_layers_1_norm1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26405184)))]; tensor encoder_transformer_transformer_layers_1_self_attn_in_proj_weight = const()[name = tensor("encoder_transformer_transformer_layers_1_self_attn_in_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26407296)))]; tensor encoder_transformer_transformer_layers_1_self_attn_out_proj_weight = const()[name = tensor("encoder_transformer_transformer_layers_1_self_attn_out_proj_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(29553088)))]; tensor encoder_transformer_transformer_layers_1_layer_scale_1_scale = const()[name = tensor("encoder_transformer_transformer_layers_1_layer_scale_1_scale"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30601728)))]; tensor encoder_transformer_transformer_layers_1_norm2_bias = const()[name = tensor("encoder_transformer_transformer_layers_1_norm2_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30603840)))]; tensor encoder_transformer_transformer_layers_1_norm2_weight = const()[name = tensor("encoder_transformer_transformer_layers_1_norm2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30605952)))]; tensor encoder_transformer_transformer_layers_1_linear1_weight = const()[name = tensor("encoder_transformer_transformer_layers_1_linear1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30608064)))]; tensor encoder_transformer_transformer_layers_1_linear2_weight = const()[name = tensor("encoder_transformer_transformer_layers_1_linear2_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(34802432)))]; tensor encoder_transformer_transformer_layers_1_layer_scale_2_scale = const()[name = tensor("encoder_transformer_transformer_layers_1_layer_scale_2_scale"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38996800)))]; tensor downsample_conv_conv_weight = const()[name = tensor("downsample_conv_conv_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38998912)))]; tensor var_8 = const()[name = tensor("op_8"), val = tensor(0x1p+0)]; tensor const_0 = const()[name = tensor("const_0"), val = tensor(0x0p+0)]; tensor input_1_pad_0 = const()[name = tensor("input_1_pad_0"), val = tensor([0, 0, 0, 0, 6, 0])]; tensor input_1_mode_0 = const()[name = tensor("input_1_mode_0"), val = tensor("constant")]; tensor input_1 = pad(constant_val = const_0, mode = input_1_mode_0, pad = input_1_pad_0, x = audio)[name = tensor("input_1")]; tensor input_3_pad_type_0 = const()[name = tensor("input_3_pad_type_0"), val = tensor("valid")]; tensor input_3_strides_0 = const()[name = tensor("input_3_strides_0"), val = tensor([1])]; tensor input_3_pad_0 = const()[name = tensor("input_3_pad_0"), val = tensor([0, 0])]; tensor input_3_dilations_0 = const()[name = tensor("input_3_dilations_0"), val = tensor([1])]; tensor input_3_groups_0 = const()[name = tensor("input_3_groups_0"), val = tensor(1)]; tensor input_3 = conv(bias = encoder_model_0_conv_bias, dilations = input_3_dilations_0, groups = input_3_groups_0, pad = input_3_pad_0, pad_type = input_3_pad_type_0, strides = input_3_strides_0, weight = encoder_model_0_conv_weight, x = input_1)[name = tensor("input_3")]; tensor input_5 = elu(alpha = var_8, x = input_3)[name = tensor("input_5")]; tensor const_1 = const()[name = tensor("const_1"), val = tensor(0x0p+0)]; tensor input_7_pad_0 = const()[name = tensor("input_7_pad_0"), val = tensor([0, 0, 0, 0, 2, 0])]; tensor input_7_mode_0 = const()[name = tensor("input_7_mode_0"), val = tensor("constant")]; tensor input_7 = pad(constant_val = const_1, mode = input_7_mode_0, pad = input_7_pad_0, x = input_5)[name = tensor("input_7")]; tensor input_9_pad_type_0 = const()[name = tensor("input_9_pad_type_0"), val = tensor("valid")]; tensor input_9_strides_0 = const()[name = tensor("input_9_strides_0"), val = tensor([1])]; tensor input_9_pad_0 = const()[name = tensor("input_9_pad_0"), val = tensor([0, 0])]; tensor input_9_dilations_0 = const()[name = tensor("input_9_dilations_0"), val = tensor([1])]; tensor input_9_groups_0 = const()[name = tensor("input_9_groups_0"), val = tensor(1)]; tensor input_9 = conv(bias = encoder_model_1_block_1_conv_bias, dilations = input_9_dilations_0, groups = input_9_groups_0, pad = input_9_pad_0, pad_type = input_9_pad_type_0, strides = input_9_strides_0, weight = encoder_model_1_block_1_conv_weight, x = input_7)[name = tensor("input_9")]; tensor input_11 = elu(alpha = var_8, x = input_9)[name = tensor("input_11")]; tensor v_1_pad_type_0 = const()[name = tensor("v_1_pad_type_0"), val = tensor("valid")]; tensor v_1_strides_0 = const()[name = tensor("v_1_strides_0"), val = tensor([1])]; tensor v_1_pad_0 = const()[name = tensor("v_1_pad_0"), val = tensor([0, 0])]; tensor v_1_dilations_0 = const()[name = tensor("v_1_dilations_0"), val = tensor([1])]; tensor v_1_groups_0 = const()[name = tensor("v_1_groups_0"), val = tensor(1)]; tensor v_1 = conv(bias = encoder_model_1_block_3_conv_bias, dilations = v_1_dilations_0, groups = v_1_groups_0, pad = v_1_pad_0, pad_type = v_1_pad_type_0, strides = v_1_strides_0, weight = encoder_model_1_block_3_conv_weight, x = input_11)[name = tensor("v_1")]; tensor input_13 = add(x = input_3, y = v_1)[name = tensor("input_13")]; tensor input_15 = elu(alpha = var_8, x = input_13)[name = tensor("input_15")]; tensor const_2 = const()[name = tensor("const_2"), val = tensor(0x0p+0)]; tensor input_17_pad_0 = const()[name = tensor("input_17_pad_0"), val = tensor([0, 0, 0, 0, 4, 0])]; tensor input_17_mode_0 = const()[name = tensor("input_17_mode_0"), val = tensor("constant")]; tensor input_17 = pad(constant_val = const_2, mode = input_17_mode_0, pad = input_17_pad_0, x = input_15)[name = tensor("input_17")]; tensor input_19_pad_type_0 = const()[name = tensor("input_19_pad_type_0"), val = tensor("valid")]; tensor input_19_strides_0 = const()[name = tensor("input_19_strides_0"), val = tensor([4])]; tensor input_19_pad_0 = const()[name = tensor("input_19_pad_0"), val = tensor([0, 0])]; tensor input_19_dilations_0 = const()[name = tensor("input_19_dilations_0"), val = tensor([1])]; tensor input_19_groups_0 = const()[name = tensor("input_19_groups_0"), val = tensor(1)]; tensor input_19 = conv(bias = encoder_model_3_conv_bias, dilations = input_19_dilations_0, groups = input_19_groups_0, pad = input_19_pad_0, pad_type = input_19_pad_type_0, strides = input_19_strides_0, weight = encoder_model_3_conv_weight, x = input_17)[name = tensor("input_19")]; tensor input_21 = elu(alpha = var_8, x = input_19)[name = tensor("input_21")]; tensor const_3 = const()[name = tensor("const_3"), val = tensor(0x0p+0)]; tensor input_23_pad_0 = const()[name = tensor("input_23_pad_0"), val = tensor([0, 0, 0, 0, 2, 0])]; tensor input_23_mode_0 = const()[name = tensor("input_23_mode_0"), val = tensor("constant")]; tensor input_23 = pad(constant_val = const_3, mode = input_23_mode_0, pad = input_23_pad_0, x = input_21)[name = tensor("input_23")]; tensor input_25_pad_type_0 = const()[name = tensor("input_25_pad_type_0"), val = tensor("valid")]; tensor input_25_strides_0 = const()[name = tensor("input_25_strides_0"), val = tensor([1])]; tensor input_25_pad_0 = const()[name = tensor("input_25_pad_0"), val = tensor([0, 0])]; tensor input_25_dilations_0 = const()[name = tensor("input_25_dilations_0"), val = tensor([1])]; tensor input_25_groups_0 = const()[name = tensor("input_25_groups_0"), val = tensor(1)]; tensor input_25 = conv(bias = encoder_model_4_block_1_conv_bias, dilations = input_25_dilations_0, groups = input_25_groups_0, pad = input_25_pad_0, pad_type = input_25_pad_type_0, strides = input_25_strides_0, weight = encoder_model_4_block_1_conv_weight, x = input_23)[name = tensor("input_25")]; tensor input_27 = elu(alpha = var_8, x = input_25)[name = tensor("input_27")]; tensor v_3_pad_type_0 = const()[name = tensor("v_3_pad_type_0"), val = tensor("valid")]; tensor v_3_strides_0 = const()[name = tensor("v_3_strides_0"), val = tensor([1])]; tensor v_3_pad_0 = const()[name = tensor("v_3_pad_0"), val = tensor([0, 0])]; tensor v_3_dilations_0 = const()[name = tensor("v_3_dilations_0"), val = tensor([1])]; tensor v_3_groups_0 = const()[name = tensor("v_3_groups_0"), val = tensor(1)]; tensor v_3 = conv(bias = encoder_model_4_block_3_conv_bias, dilations = v_3_dilations_0, groups = v_3_groups_0, pad = v_3_pad_0, pad_type = v_3_pad_type_0, strides = v_3_strides_0, weight = encoder_model_4_block_3_conv_weight, x = input_27)[name = tensor("v_3")]; tensor input_29 = add(x = input_19, y = v_3)[name = tensor("input_29")]; tensor input_31 = elu(alpha = var_8, x = input_29)[name = tensor("input_31")]; tensor const_4 = const()[name = tensor("const_4"), val = tensor(0x0p+0)]; tensor input_33_pad_0 = const()[name = tensor("input_33_pad_0"), val = tensor([0, 0, 0, 0, 5, 0])]; tensor input_33_mode_0 = const()[name = tensor("input_33_mode_0"), val = tensor("constant")]; tensor input_33 = pad(constant_val = const_4, mode = input_33_mode_0, pad = input_33_pad_0, x = input_31)[name = tensor("input_33")]; tensor input_35_pad_type_0 = const()[name = tensor("input_35_pad_type_0"), val = tensor("valid")]; tensor input_35_strides_0 = const()[name = tensor("input_35_strides_0"), val = tensor([5])]; tensor input_35_pad_0 = const()[name = tensor("input_35_pad_0"), val = tensor([0, 0])]; tensor input_35_dilations_0 = const()[name = tensor("input_35_dilations_0"), val = tensor([1])]; tensor input_35_groups_0 = const()[name = tensor("input_35_groups_0"), val = tensor(1)]; tensor input_35 = conv(bias = encoder_model_6_conv_bias, dilations = input_35_dilations_0, groups = input_35_groups_0, pad = input_35_pad_0, pad_type = input_35_pad_type_0, strides = input_35_strides_0, weight = encoder_model_6_conv_weight, x = input_33)[name = tensor("input_35")]; tensor input_37 = elu(alpha = var_8, x = input_35)[name = tensor("input_37")]; tensor const_5 = const()[name = tensor("const_5"), val = tensor(0x0p+0)]; tensor input_39_pad_0 = const()[name = tensor("input_39_pad_0"), val = tensor([0, 0, 0, 0, 2, 0])]; tensor input_39_mode_0 = const()[name = tensor("input_39_mode_0"), val = tensor("constant")]; tensor input_39 = pad(constant_val = const_5, mode = input_39_mode_0, pad = input_39_pad_0, x = input_37)[name = tensor("input_39")]; tensor input_41_pad_type_0 = const()[name = tensor("input_41_pad_type_0"), val = tensor("valid")]; tensor input_41_strides_0 = const()[name = tensor("input_41_strides_0"), val = tensor([1])]; tensor input_41_pad_0 = const()[name = tensor("input_41_pad_0"), val = tensor([0, 0])]; tensor input_41_dilations_0 = const()[name = tensor("input_41_dilations_0"), val = tensor([1])]; tensor input_41_groups_0 = const()[name = tensor("input_41_groups_0"), val = tensor(1)]; tensor input_41 = conv(bias = encoder_model_7_block_1_conv_bias, dilations = input_41_dilations_0, groups = input_41_groups_0, pad = input_41_pad_0, pad_type = input_41_pad_type_0, strides = input_41_strides_0, weight = encoder_model_7_block_1_conv_weight, x = input_39)[name = tensor("input_41")]; tensor input_43 = elu(alpha = var_8, x = input_41)[name = tensor("input_43")]; tensor v_pad_type_0 = const()[name = tensor("v_pad_type_0"), val = tensor("valid")]; tensor v_strides_0 = const()[name = tensor("v_strides_0"), val = tensor([1])]; tensor v_pad_0 = const()[name = tensor("v_pad_0"), val = tensor([0, 0])]; tensor v_dilations_0 = const()[name = tensor("v_dilations_0"), val = tensor([1])]; tensor v_groups_0 = const()[name = tensor("v_groups_0"), val = tensor(1)]; tensor v = conv(bias = encoder_model_7_block_3_conv_bias, dilations = v_dilations_0, groups = v_groups_0, pad = v_pad_0, pad_type = v_pad_type_0, strides = v_strides_0, weight = encoder_model_7_block_3_conv_weight, x = input_43)[name = tensor("v")]; tensor input_45 = add(x = input_35, y = v)[name = tensor("input_45")]; tensor input_47 = elu(alpha = var_8, x = input_45)[name = tensor("input_47")]; tensor const_6 = const()[name = tensor("const_6"), val = tensor(0x0p+0)]; tensor input_49_pad_0 = const()[name = tensor("input_49_pad_0"), val = tensor([0, 0, 0, 0, 6, 0])]; tensor input_49_mode_0 = const()[name = tensor("input_49_mode_0"), val = tensor("constant")]; tensor input_49 = pad(constant_val = const_6, mode = input_49_mode_0, pad = input_49_pad_0, x = input_47)[name = tensor("input_49")]; tensor input_51_pad_type_0 = const()[name = tensor("input_51_pad_type_0"), val = tensor("valid")]; tensor input_51_strides_0 = const()[name = tensor("input_51_strides_0"), val = tensor([6])]; tensor input_51_pad_0 = const()[name = tensor("input_51_pad_0"), val = tensor([0, 0])]; tensor input_51_dilations_0 = const()[name = tensor("input_51_dilations_0"), val = tensor([1])]; tensor input_51_groups_0 = const()[name = tensor("input_51_groups_0"), val = tensor(1)]; tensor input_51 = conv(bias = encoder_model_9_conv_bias, dilations = input_51_dilations_0, groups = input_51_groups_0, pad = input_51_pad_0, pad_type = input_51_pad_type_0, strides = input_51_strides_0, weight = encoder_model_9_conv_weight, x = input_49)[name = tensor("input_51")]; tensor input_53 = elu(alpha = var_8, x = input_51)[name = tensor("input_53")]; tensor const_7 = const()[name = tensor("const_7"), val = tensor(0x0p+0)]; tensor input_55_pad_0 = const()[name = tensor("input_55_pad_0"), val = tensor([0, 0, 0, 0, 2, 0])]; tensor input_55_mode_0 = const()[name = tensor("input_55_mode_0"), val = tensor("constant")]; tensor input_55 = pad(constant_val = const_7, mode = input_55_mode_0, pad = input_55_pad_0, x = input_53)[name = tensor("input_55")]; tensor x_1_pad_type_0 = const()[name = tensor("x_1_pad_type_0"), val = tensor("valid")]; tensor x_1_strides_0 = const()[name = tensor("x_1_strides_0"), val = tensor([1])]; tensor x_1_pad_0 = const()[name = tensor("x_1_pad_0"), val = tensor([0, 0])]; tensor x_1_dilations_0 = const()[name = tensor("x_1_dilations_0"), val = tensor([1])]; tensor x_1_groups_0 = const()[name = tensor("x_1_groups_0"), val = tensor(1)]; tensor x_1 = conv(bias = encoder_model_11_conv_bias, dilations = x_1_dilations_0, groups = x_1_groups_0, pad = x_1_pad_0, pad_type = x_1_pad_type_0, strides = x_1_strides_0, weight = encoder_model_11_conv_weight, x = input_55)[name = tensor("x_1")]; tensor var_163 = const()[name = tensor("op_163"), val = tensor(0)]; tensor var_169 = const()[name = tensor("op_169"), val = tensor(3)]; tensor var_170 = const()[name = tensor("op_170"), val = tensor(8)]; tensor var_171 = const()[name = tensor("op_171"), val = tensor(-1)]; tensor var_175 = const()[name = tensor("op_175"), val = tensor(250)]; tensor var_178 = const()[name = tensor("op_178"), val = tensor(0x1.4f8b58p-17)]; tensor var_180 = const()[name = tensor("op_180"), val = tensor(2)]; tensor input_57_perm_0 = const()[name = tensor("input_57_perm_0"), val = tensor([0, 2, 1])]; tensor query_1_axes_0 = const()[name = tensor("query_1_axes_0"), val = tensor([-1])]; tensor input_57 = transpose(perm = input_57_perm_0, x = x_1)[name = tensor("transpose_14")]; tensor query_1 = layer_norm(axes = query_1_axes_0, beta = encoder_transformer_transformer_layers_0_norm1_bias, epsilon = var_178, gamma = encoder_transformer_transformer_layers_0_norm1_weight, x = input_57)[name = tensor("query_1")]; tensor var_202_shape = shape(x = query_1)[name = tensor("op_202_shape")]; tensor gather_1_batch_dims_0 = const()[name = tensor("gather_1_batch_dims_0"), val = tensor(0)]; tensor gather_1_validate_indices_0 = const()[name = tensor("gather_1_validate_indices_0"), val = tensor(false)]; tensor select_3 = const()[name = tensor("select_3"), val = tensor(1)]; tensor gather_1_axis_1 = const()[name = tensor("gather_1_axis_1"), val = tensor(0)]; tensor gather_1 = gather(axis = gather_1_axis_1, batch_dims = gather_1_batch_dims_0, indices = select_3, validate_indices = gather_1_validate_indices_0, x = var_202_shape)[name = tensor("gather_1")]; tensor linear_0_bias_0 = const()[name = tensor("linear_0_bias_0"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72553408)))]; tensor x_3 = linear(bias = linear_0_bias_0, weight = encoder_transformer_transformer_layers_0_self_attn_in_proj_weight, x = query_1)[name = tensor("linear_0")]; tensor concat_0x = const()[name = tensor("concat_0x"), val = tensor([1, -1, 3, 8, 64])]; tensor x_5 = reshape(shape = concat_0x, x = x_3)[name = tensor("x_5")]; tensor var_215 = const()[name = tensor("op_215"), val = tensor([2, 0, 3, 1, 4])]; tensor var_217_split_sizes_0 = const()[name = tensor("op_217_split_sizes_0"), val = tensor([1, 1, 1])]; tensor var_217_axis_0 = const()[name = tensor("op_217_axis_0"), val = tensor(0)]; tensor var_216 = transpose(perm = var_215, x = x_5)[name = tensor("transpose_13")]; tensor var_217_0, tensor var_217_1, tensor var_217_2 = split(axis = var_217_axis_0, split_sizes = var_217_split_sizes_0, x = var_216)[name = tensor("op_217")]; tensor squeeze_0_axes_0 = const()[name = tensor("squeeze_0_axes_0"), val = tensor([0])]; tensor squeeze_0 = squeeze(axes = squeeze_0_axes_0, x = var_217_0)[name = tensor("squeeze_0")]; tensor squeeze_1_axes_0 = const()[name = tensor("squeeze_1_axes_0"), val = tensor([0])]; tensor squeeze_1 = squeeze(axes = squeeze_1_axes_0, x = var_217_1)[name = tensor("squeeze_1")]; tensor squeeze_2_axes_0 = const()[name = tensor("squeeze_2_axes_0"), val = tensor([0])]; tensor squeeze_2 = squeeze(axes = squeeze_2_axes_0, x = var_217_2)[name = tensor("squeeze_2")]; tensor var_221 = const()[name = tensor("op_221"), val = tensor([0, 2, 1, 3])]; tensor var_223 = const()[name = tensor("op_223"), val = tensor([0, 2, 1, 3])]; tensor q_3 = transpose(perm = var_221, x = squeeze_0)[name = tensor("transpose_12")]; tensor var_225_shape = shape(x = q_3)[name = tensor("op_225_shape")]; tensor gather_6_batch_dims_0 = const()[name = tensor("gather_6_batch_dims_0"), val = tensor(0)]; tensor gather_6_validate_indices_0 = const()[name = tensor("gather_6_validate_indices_0"), val = tensor(false)]; tensor select_5 = const()[name = tensor("select_5"), val = tensor(1)]; tensor gather_6_axis_1 = const()[name = tensor("gather_6_axis_1"), val = tensor(0)]; tensor gather_6 = gather(axis = gather_6_axis_1, batch_dims = gather_6_batch_dims_0, indices = select_5, validate_indices = gather_6_validate_indices_0, x = var_225_shape)[name = tensor("gather_6")]; tensor freqs_1 = const()[name = tensor("freqs_1"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72559616)))]; tensor const_10 = const()[name = tensor("const_10"), val = tensor(0)]; tensor const_11 = const()[name = tensor("const_11"), val = tensor(1)]; tensor ts_1 = range_1d(end = gather_6, start = const_10, step = const_11)[name = tensor("ts_1")]; tensor var_239 = const()[name = tensor("op_239"), val = tensor([-1, 1, 1])]; tensor ts_5 = reshape(shape = var_239, x = ts_1)[name = tensor("ts_5")]; tensor concat_1x = const()[name = tensor("concat_1x"), val = tensor([1, -1, 8, 32, 2])]; tensor q_5 = reshape(shape = concat_1x, x = q_3)[name = tensor("q_5")]; tensor concat_2x = const()[name = tensor("concat_2x"), val = tensor([1, -1, 8, 32, 2])]; tensor k_3 = transpose(perm = var_223, x = squeeze_1)[name = tensor("transpose_11")]; tensor k_5 = reshape(shape = concat_2x, x = k_3)[name = tensor("k_5")]; tensor var_249_begin_0 = const()[name = tensor("op_249_begin_0"), val = tensor([0, 0, 0, 0, 0])]; tensor var_249_end_0 = const()[name = tensor("op_249_end_0"), val = tensor([1, 0, 8, 32, 1])]; tensor var_249_end_mask_0 = const()[name = tensor("op_249_end_mask_0"), val = tensor([true, true, true, true, false])]; tensor var_249_squeeze_mask_0 = const()[name = tensor("op_249_squeeze_mask_0"), val = tensor([false, false, false, false, true])]; tensor var_249 = slice_by_index(begin = var_249_begin_0, end = var_249_end_0, end_mask = var_249_end_mask_0, squeeze_mask = var_249_squeeze_mask_0, x = q_5)[name = tensor("op_249")]; tensor var_251_begin_0 = const()[name = tensor("op_251_begin_0"), val = tensor([0, 0, 0, 0, 1])]; tensor var_251_end_0 = const()[name = tensor("op_251_end_0"), val = tensor([1, 0, 8, 32, 2])]; tensor var_251_end_mask_0 = const()[name = tensor("op_251_end_mask_0"), val = tensor([true, true, true, true, false])]; tensor var_251_squeeze_mask_0 = const()[name = tensor("op_251_squeeze_mask_0"), val = tensor([false, false, false, false, true])]; tensor var_251 = slice_by_index(begin = var_251_begin_0, end = var_251_end_0, end_mask = var_251_end_mask_0, squeeze_mask = var_251_squeeze_mask_0, x = q_5)[name = tensor("op_251")]; tensor var_253_begin_0 = const()[name = tensor("op_253_begin_0"), val = tensor([0, 0, 0, 0, 0])]; tensor var_253_end_0 = const()[name = tensor("op_253_end_0"), val = tensor([1, 0, 8, 32, 1])]; tensor var_253_end_mask_0 = const()[name = tensor("op_253_end_mask_0"), val = tensor([true, true, true, true, false])]; tensor var_253_squeeze_mask_0 = const()[name = tensor("op_253_squeeze_mask_0"), val = tensor([false, false, false, false, true])]; tensor var_253 = slice_by_index(begin = var_253_begin_0, end = var_253_end_0, end_mask = var_253_end_mask_0, squeeze_mask = var_253_squeeze_mask_0, x = k_5)[name = tensor("op_253")]; tensor var_255_begin_0 = const()[name = tensor("op_255_begin_0"), val = tensor([0, 0, 0, 0, 1])]; tensor var_255_end_0 = const()[name = tensor("op_255_end_0"), val = tensor([1, 0, 8, 32, 2])]; tensor var_255_end_mask_0 = const()[name = tensor("op_255_end_mask_0"), val = tensor([true, true, true, true, false])]; tensor var_255_squeeze_mask_0 = const()[name = tensor("op_255_squeeze_mask_0"), val = tensor([false, false, false, false, true])]; tensor var_255 = slice_by_index(begin = var_255_begin_0, end = var_255_end_0, end_mask = var_255_end_mask_0, squeeze_mask = var_255_squeeze_mask_0, x = k_5)[name = tensor("op_255")]; tensor ts_5_promoted_dtype_0 = const()[name = tensor("ts_5_promoted_dtype_0"), val = tensor("fp32")]; tensor ts_5_promoted = cast(dtype = ts_5_promoted_dtype_0, x = ts_5)[name = tensor("cast_34")]; tensor var_257 = mul(x = freqs_1, y = ts_5_promoted)[name = tensor("op_257")]; tensor rotr_1 = cos(x = var_257)[name = tensor("rotr_1")]; tensor roti_1 = sin(x = var_257)[name = tensor("roti_1")]; tensor var_261 = mul(x = var_249, y = rotr_1)[name = tensor("op_261")]; tensor var_262 = mul(x = var_251, y = roti_1)[name = tensor("op_262")]; tensor qor_1 = sub(x = var_261, y = var_262)[name = tensor("qor_1")]; tensor var_264 = mul(x = var_249, y = roti_1)[name = tensor("op_264")]; tensor var_265 = mul(x = var_251, y = rotr_1)[name = tensor("op_265")]; tensor qoi_1 = add(x = var_264, y = var_265)[name = tensor("qoi_1")]; tensor var_267 = mul(x = var_253, y = rotr_1)[name = tensor("op_267")]; tensor var_268 = mul(x = var_255, y = roti_1)[name = tensor("op_268")]; tensor kor_1 = sub(x = var_267, y = var_268)[name = tensor("kor_1")]; tensor var_270 = mul(x = var_253, y = roti_1)[name = tensor("op_270")]; tensor var_271 = mul(x = var_255, y = rotr_1)[name = tensor("op_271")]; tensor koi_1 = add(x = var_270, y = var_271)[name = tensor("koi_1")]; tensor qo_1_axis_0 = const()[name = tensor("qo_1_axis_0"), val = tensor(-1)]; tensor qo_1 = stack(axis = qo_1_axis_0, values = (qor_1, qoi_1))[name = tensor("qo_1")]; tensor ko_1_axis_0 = const()[name = tensor("ko_1_axis_0"), val = tensor(-1)]; tensor ko_1 = stack(axis = ko_1_axis_0, values = (kor_1, koi_1))[name = tensor("ko_1")]; tensor concat_3x = const()[name = tensor("concat_3x"), val = tensor([1, -1, 8, 64])]; tensor q_7 = reshape(shape = concat_3x, x = qo_1)[name = tensor("q_7")]; tensor concat_4x = const()[name = tensor("concat_4x"), val = tensor([1, -1, 8, 64])]; tensor k_7 = reshape(shape = concat_4x, x = ko_1)[name = tensor("k_7")]; tensor var_288 = const()[name = tensor("op_288"), val = tensor([0, 2, 1, 3])]; tensor var_290 = const()[name = tensor("op_290"), val = tensor([0, 2, 1, 3])]; tensor keys_1 = transpose(perm = var_290, x = k_7)[name = tensor("transpose_9")]; tensor var_293_shape = shape(x = keys_1)[name = tensor("op_293_shape")]; tensor gather_11_batch_dims_0 = const()[name = tensor("gather_11_batch_dims_0"), val = tensor(0)]; tensor gather_11_validate_indices_0 = const()[name = tensor("gather_11_validate_indices_0"), val = tensor(false)]; tensor select_6 = const()[name = tensor("select_6"), val = tensor(2)]; tensor gather_11_axis_1 = const()[name = tensor("gather_11_axis_1"), val = tensor(0)]; tensor gather_11 = gather(axis = gather_11_axis_1, batch_dims = gather_11_batch_dims_0, indices = select_6, validate_indices = gather_11_validate_indices_0, x = var_293_shape)[name = tensor("gather_11")]; tensor const_12 = const()[name = tensor("const_12"), val = tensor(0)]; tensor const_13 = const()[name = tensor("const_13"), val = tensor(1)]; tensor positions_1 = range_1d(end = gather_11, start = const_12, step = const_13)[name = tensor("positions_1")]; tensor concat_5 = const()[name = tensor("concat_5"), val = tensor([1, -1])]; tensor expand_dims_0_axes_0 = const()[name = tensor("expand_dims_0_axes_0"), val = tensor([0])]; tensor expand_dims_0 = expand_dims(axes = expand_dims_0_axes_0, x = positions_1)[name = tensor("expand_dims_0")]; tensor shape_0 = shape(x = expand_dims_0)[name = tensor("shape_0")]; tensor equal_0 = const()[name = tensor("equal_0"), val = tensor([false, true])]; tensor select_0 = select(a = shape_0, b = concat_5, cond = equal_0)[name = tensor("select_0")]; tensor real_div_0 = real_div(x = select_0, y = shape_0)[name = tensor("real_div_0")]; tensor pos_k_1 = tile(reps = real_div_0, x = expand_dims_0)[name = tensor("pos_k_1")]; tensor pos_k_3_axes_0 = const()[name = tensor("pos_k_3_axes_0"), val = tensor([1])]; tensor pos_k_3 = expand_dims(axes = pos_k_3_axes_0, x = pos_k_1)[name = tensor("pos_k_3")]; tensor var_300 = const()[name = tensor("op_300"), val = tensor([[[0]]])]; tensor const_14 = const()[name = tensor("const_14"), val = tensor(0)]; tensor const_15 = const()[name = tensor("const_15"), val = tensor(1)]; tensor var_301 = range_1d(end = gather_1, start = const_14, step = const_15)[name = tensor("op_301")]; tensor var_302 = const()[name = tensor("op_302"), val = tensor([-1, 1])]; tensor var_303 = reshape(shape = var_302, x = var_301)[name = tensor("op_303")]; tensor pos_q_1 = add(x = var_300, y = var_303)[name = tensor("pos_q_1")]; tensor delta_1 = sub(x = pos_q_1, y = pos_k_3)[name = tensor("delta_1")]; tensor var_306 = greater_equal(x = pos_k_3, y = var_163)[name = tensor("op_306")]; tensor var_307 = greater_equal(x = delta_1, y = var_163)[name = tensor("op_307")]; tensor attn_bias_1 = logical_and(x = var_306, y = var_307)[name = tensor("attn_bias_1")]; tensor var_309 = less(x = delta_1, y = var_175)[name = tensor("op_309")]; tensor attn_bias_3 = logical_and(x = attn_bias_1, y = var_309)[name = tensor("attn_bias_3")]; tensor attn_bias_5_axes_0 = const()[name = tensor("attn_bias_5_axes_0"), val = tensor([1])]; tensor attn_bias_5 = expand_dims(axes = attn_bias_5_axes_0, x = attn_bias_3)[name = tensor("attn_bias_5")]; tensor cast_13_dtype_0 = const()[name = tensor("cast_13_dtype_0"), val = tensor("fp32")]; tensor sub_0_x_0 = const()[name = tensor("sub_0_x_0"), val = tensor(0x1p+0)]; tensor cast_13 = cast(dtype = cast_13_dtype_0, x = attn_bias_5)[name = tensor("cast_33")]; tensor sub_0 = sub(x = sub_0_x_0, y = cast_13)[name = tensor("sub_0")]; tensor mul_0_x_0 = const()[name = tensor("mul_0_x_0"), val = tensor(-0x1.d4cp+14)]; tensor mul_0 = mul(x = mul_0_x_0, y = sub_0)[name = tensor("mul_0")]; tensor mul_1_y_0 = const()[name = tensor("mul_1_y_0"), val = tensor(0x1p-3)]; tensor q_9 = transpose(perm = var_288, x = q_7)[name = tensor("transpose_10")]; tensor mul_1 = mul(x = q_9, y = mul_1_y_0)[name = tensor("mul_1")]; tensor matmul_0_transpose_y_0 = const()[name = tensor("matmul_0_transpose_y_0"), val = tensor(true)]; tensor matmul_0_transpose_x_0 = const()[name = tensor("matmul_0_transpose_x_0"), val = tensor(false)]; tensor matmul_0 = matmul(transpose_x = matmul_0_transpose_x_0, transpose_y = matmul_0_transpose_y_0, x = mul_1, y = keys_1)[name = tensor("matmul_0")]; tensor add_0 = add(x = matmul_0, y = mul_0)[name = tensor("add_0")]; tensor softmax_0_axis_0 = const()[name = tensor("softmax_0_axis_0"), val = tensor(-1)]; tensor softmax_0 = softmax(axis = softmax_0_axis_0, x = add_0)[name = tensor("softmax_0")]; tensor x_7_transpose_x_0 = const()[name = tensor("x_7_transpose_x_0"), val = tensor(false)]; tensor x_7_transpose_y_0 = const()[name = tensor("x_7_transpose_y_0"), val = tensor(false)]; tensor x_7 = matmul(transpose_x = x_7_transpose_x_0, transpose_y = x_7_transpose_y_0, x = softmax_0, y = squeeze_2)[name = tensor("x_7")]; tensor var_314_shape = shape(x = x_7)[name = tensor("op_314_shape")]; tensor gather_12_batch_dims_0 = const()[name = tensor("gather_12_batch_dims_0"), val = tensor(0)]; tensor gather_12_validate_indices_0 = const()[name = tensor("gather_12_validate_indices_0"), val = tensor(false)]; tensor select_7 = const()[name = tensor("select_7"), val = tensor(0)]; tensor gather_12_axis_1 = const()[name = tensor("gather_12_axis_1"), val = tensor(0)]; tensor gather_12 = gather(axis = gather_12_axis_1, batch_dims = gather_12_batch_dims_0, indices = select_7, validate_indices = gather_12_validate_indices_0, x = var_314_shape)[name = tensor("gather_12")]; tensor gather_14_batch_dims_0 = const()[name = tensor("gather_14_batch_dims_0"), val = tensor(0)]; tensor gather_14_validate_indices_0 = const()[name = tensor("gather_14_validate_indices_0"), val = tensor(false)]; tensor select_8 = const()[name = tensor("select_8"), val = tensor(2)]; tensor gather_14_axis_1 = const()[name = tensor("gather_14_axis_1"), val = tensor(0)]; tensor gather_14 = gather(axis = gather_14_axis_1, batch_dims = gather_14_batch_dims_0, indices = select_8, validate_indices = gather_14_validate_indices_0, x = var_314_shape)[name = tensor("gather_14")]; tensor var_331 = const()[name = tensor("op_331"), val = tensor(512)]; tensor var_332 = const()[name = tensor("op_332"), val = tensor([0, 2, 1, 3])]; tensor concat_6_axis_0 = const()[name = tensor("concat_6_axis_0"), val = tensor(0)]; tensor concat_6_interleave_0 = const()[name = tensor("concat_6_interleave_0"), val = tensor(false)]; tensor concat_6 = concat(axis = concat_6_axis_0, interleave = concat_6_interleave_0, values = (gather_12, gather_14, var_331))[name = tensor("concat_6")]; tensor x_9 = transpose(perm = var_332, x = x_7)[name = tensor("transpose_8")]; tensor input_59 = reshape(shape = concat_6, x = x_9)[name = tensor("input_59")]; tensor linear_1_bias_0 = const()[name = tensor("linear_1_bias_0"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72559808)))]; tensor x_11 = linear(bias = linear_1_bias_0, weight = encoder_transformer_transformer_layers_0_self_attn_out_proj_weight, x = input_59)[name = tensor("linear_1")]; tensor var_340 = mul(x = encoder_transformer_transformer_layers_0_layer_scale_1_scale, y = x_11)[name = tensor("op_340")]; tensor input_61 = add(x = input_57, y = var_340)[name = tensor("input_61")]; tensor input_63_axes_0 = const()[name = tensor("input_63_axes_0"), val = tensor([-1])]; tensor input_63 = layer_norm(axes = input_63_axes_0, beta = encoder_transformer_transformer_layers_0_norm2_bias, epsilon = var_178, gamma = encoder_transformer_transformer_layers_0_norm2_weight, x = input_61)[name = tensor("input_63")]; tensor linear_2_bias_0 = const()[name = tensor("linear_2_bias_0"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72561920)))]; tensor var_347 = linear(bias = linear_2_bias_0, weight = encoder_transformer_transformer_layers_0_linear1_weight, x = input_63)[name = tensor("linear_2")]; tensor input_65_mode_0 = const()[name = tensor("input_65_mode_0"), val = tensor("EXACT")]; tensor input_65 = gelu(mode = input_65_mode_0, x = var_347)[name = tensor("input_65")]; tensor x_13 = linear(bias = linear_1_bias_0, weight = encoder_transformer_transformer_layers_0_linear2_weight, x = input_65)[name = tensor("linear_3")]; tensor var_353 = mul(x = encoder_transformer_transformer_layers_0_layer_scale_2_scale, y = x_13)[name = tensor("op_353")]; tensor input_67 = add(x = input_61, y = var_353)[name = tensor("input_67")]; tensor query_axes_0 = const()[name = tensor("query_axes_0"), val = tensor([-1])]; tensor query = layer_norm(axes = query_axes_0, beta = encoder_transformer_transformer_layers_1_norm1_bias, epsilon = var_178, gamma = encoder_transformer_transformer_layers_1_norm1_weight, x = input_67)[name = tensor("query")]; tensor var_368_shape = shape(x = query)[name = tensor("op_368_shape")]; tensor gather_16_batch_dims_0 = const()[name = tensor("gather_16_batch_dims_0"), val = tensor(0)]; tensor gather_16_validate_indices_0 = const()[name = tensor("gather_16_validate_indices_0"), val = tensor(false)]; tensor select_9 = const()[name = tensor("select_9"), val = tensor(0)]; tensor gather_16_axis_1 = const()[name = tensor("gather_16_axis_1"), val = tensor(0)]; tensor gather_16 = gather(axis = gather_16_axis_1, batch_dims = gather_16_batch_dims_0, indices = select_9, validate_indices = gather_16_validate_indices_0, x = var_368_shape)[name = tensor("gather_16")]; tensor gather_17_batch_dims_0 = const()[name = tensor("gather_17_batch_dims_0"), val = tensor(0)]; tensor gather_17_validate_indices_0 = const()[name = tensor("gather_17_validate_indices_0"), val = tensor(false)]; tensor select_10 = const()[name = tensor("select_10"), val = tensor(1)]; tensor gather_17_axis_1 = const()[name = tensor("gather_17_axis_1"), val = tensor(0)]; tensor gather_17 = gather(axis = gather_17_axis_1, batch_dims = gather_17_batch_dims_0, indices = select_10, validate_indices = gather_17_validate_indices_0, x = var_368_shape)[name = tensor("gather_17")]; tensor concat_7_axis_0 = const()[name = tensor("concat_7_axis_0"), val = tensor(0)]; tensor concat_7_interleave_0 = const()[name = tensor("concat_7_interleave_0"), val = tensor(false)]; tensor concat_7 = concat(axis = concat_7_axis_0, interleave = concat_7_interleave_0, values = gather_16)[name = tensor("concat_7")]; tensor offset_value_0 = const()[name = tensor("offset_value_0"), val = tensor(0)]; tensor offset = fill(shape = concat_7, value = offset_value_0)[name = tensor("offset")]; tensor x_15 = linear(bias = linear_0_bias_0, weight = encoder_transformer_transformer_layers_1_self_attn_in_proj_weight, x = query)[name = tensor("linear_4")]; tensor var_374_shape = shape(x = x_15)[name = tensor("op_374_shape")]; tensor gather_18_batch_dims_0 = const()[name = tensor("gather_18_batch_dims_0"), val = tensor(0)]; tensor gather_18_validate_indices_0 = const()[name = tensor("gather_18_validate_indices_0"), val = tensor(false)]; tensor select_11 = const()[name = tensor("select_11"), val = tensor(0)]; tensor gather_18_axis_1 = const()[name = tensor("gather_18_axis_1"), val = tensor(0)]; tensor gather_18 = gather(axis = gather_18_axis_1, batch_dims = gather_18_batch_dims_0, indices = select_11, validate_indices = gather_18_validate_indices_0, x = var_374_shape)[name = tensor("gather_18")]; tensor gather_19_batch_dims_0 = const()[name = tensor("gather_19_batch_dims_0"), val = tensor(0)]; tensor gather_19_validate_indices_0 = const()[name = tensor("gather_19_validate_indices_0"), val = tensor(false)]; tensor select_12 = const()[name = tensor("select_12"), val = tensor(1)]; tensor gather_19_axis_1 = const()[name = tensor("gather_19_axis_1"), val = tensor(0)]; tensor gather_19 = gather(axis = gather_19_axis_1, batch_dims = gather_19_batch_dims_0, indices = select_12, validate_indices = gather_19_validate_indices_0, x = var_374_shape)[name = tensor("gather_19")]; tensor var_379 = const()[name = tensor("op_379"), val = tensor(64)]; tensor concat_8_axis_0 = const()[name = tensor("concat_8_axis_0"), val = tensor(0)]; tensor concat_8_interleave_0 = const()[name = tensor("concat_8_interleave_0"), val = tensor(false)]; tensor concat_8 = concat(axis = concat_8_axis_0, interleave = concat_8_interleave_0, values = (gather_18, gather_19, var_169, var_170, var_379))[name = tensor("concat_8")]; tensor x_17 = reshape(shape = concat_8, x = x_15)[name = tensor("x_17")]; tensor var_382 = const()[name = tensor("op_382"), val = tensor([2, 0, 3, 1, 4])]; tensor var_384_split_sizes_0 = const()[name = tensor("op_384_split_sizes_0"), val = tensor([1, 1, 1])]; tensor var_384_axis_0 = const()[name = tensor("op_384_axis_0"), val = tensor(0)]; tensor var_383 = transpose(perm = var_382, x = x_17)[name = tensor("transpose_7")]; tensor var_384_0, tensor var_384_1, tensor var_384_2 = split(axis = var_384_axis_0, split_sizes = var_384_split_sizes_0, x = var_383)[name = tensor("op_384")]; tensor squeeze_3_axes_0 = const()[name = tensor("squeeze_3_axes_0"), val = tensor([0])]; tensor squeeze_3 = squeeze(axes = squeeze_3_axes_0, x = var_384_0)[name = tensor("squeeze_3")]; tensor squeeze_4_axes_0 = const()[name = tensor("squeeze_4_axes_0"), val = tensor([0])]; tensor squeeze_4 = squeeze(axes = squeeze_4_axes_0, x = var_384_1)[name = tensor("squeeze_4")]; tensor squeeze_5_axes_0 = const()[name = tensor("squeeze_5_axes_0"), val = tensor([0])]; tensor squeeze_5 = squeeze(axes = squeeze_5_axes_0, x = var_384_2)[name = tensor("squeeze_5")]; tensor var_388 = const()[name = tensor("op_388"), val = tensor([0, 2, 1, 3])]; tensor var_390 = const()[name = tensor("op_390"), val = tensor([0, 2, 1, 3])]; tensor q_13 = transpose(perm = var_388, x = squeeze_3)[name = tensor("transpose_6")]; tensor var_392_shape = shape(x = q_13)[name = tensor("op_392_shape")]; tensor gather_21_batch_dims_0 = const()[name = tensor("gather_21_batch_dims_0"), val = tensor(0)]; tensor gather_21_validate_indices_0 = const()[name = tensor("gather_21_validate_indices_0"), val = tensor(false)]; tensor select_13 = const()[name = tensor("select_13"), val = tensor(0)]; tensor gather_21_axis_1 = const()[name = tensor("gather_21_axis_1"), val = tensor(0)]; tensor gather_21 = gather(axis = gather_21_axis_1, batch_dims = gather_21_batch_dims_0, indices = select_13, validate_indices = gather_21_validate_indices_0, x = var_392_shape)[name = tensor("gather_21")]; tensor gather_22_batch_dims_0 = const()[name = tensor("gather_22_batch_dims_0"), val = tensor(0)]; tensor gather_22_validate_indices_0 = const()[name = tensor("gather_22_validate_indices_0"), val = tensor(false)]; tensor select_14 = const()[name = tensor("select_14"), val = tensor(1)]; tensor gather_22_axis_1 = const()[name = tensor("gather_22_axis_1"), val = tensor(0)]; tensor gather_22 = gather(axis = gather_22_axis_1, batch_dims = gather_22_batch_dims_0, indices = select_14, validate_indices = gather_22_validate_indices_0, x = var_392_shape)[name = tensor("gather_22")]; tensor gather_23 = const()[name = tensor("gather_23"), val = tensor(8)]; tensor gather_24 = const()[name = tensor("gather_24"), val = tensor(64)]; tensor freqs = const()[name = tensor("freqs"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72570176)))]; tensor const_18 = const()[name = tensor("const_18"), val = tensor(0)]; tensor const_19 = const()[name = tensor("const_19"), val = tensor(1)]; tensor ts_7 = range_1d(end = gather_22, start = const_18, step = const_19)[name = tensor("ts_7")]; tensor ts_9 = add(x = ts_7, y = offset)[name = tensor("ts_9")]; tensor var_406 = const()[name = tensor("op_406"), val = tensor([-1, 1, 1])]; tensor ts = reshape(shape = var_406, x = ts_9)[name = tensor("ts")]; tensor var_409 = const()[name = tensor("op_409"), val = tensor(32)]; tensor concat_9_axis_0 = const()[name = tensor("concat_9_axis_0"), val = tensor(0)]; tensor concat_9_interleave_0 = const()[name = tensor("concat_9_interleave_0"), val = tensor(false)]; tensor concat_9 = concat(axis = concat_9_axis_0, interleave = concat_9_interleave_0, values = (gather_21, gather_22, gather_23, var_409, var_180))[name = tensor("concat_9")]; tensor q_15 = reshape(shape = concat_9, x = q_13)[name = tensor("q_15")]; tensor k_11 = transpose(perm = var_390, x = squeeze_4)[name = tensor("transpose_5")]; tensor k_13 = reshape(shape = concat_9, x = k_11)[name = tensor("k_13")]; tensor var_416_begin_0 = const()[name = tensor("op_416_begin_0"), val = tensor([0, 0, 0, 0, 0])]; tensor var_416_end_0 = const()[name = tensor("op_416_end_0"), val = tensor([0, 0, 8, 32, 1])]; tensor var_416_end_mask_0 = const()[name = tensor("op_416_end_mask_0"), val = tensor([true, true, true, true, false])]; tensor var_416_squeeze_mask_0 = const()[name = tensor("op_416_squeeze_mask_0"), val = tensor([false, false, false, false, true])]; tensor var_416 = slice_by_index(begin = var_416_begin_0, end = var_416_end_0, end_mask = var_416_end_mask_0, squeeze_mask = var_416_squeeze_mask_0, x = q_15)[name = tensor("op_416")]; tensor var_418_begin_0 = const()[name = tensor("op_418_begin_0"), val = tensor([0, 0, 0, 0, 1])]; tensor var_418_end_0 = const()[name = tensor("op_418_end_0"), val = tensor([0, 0, 8, 32, 2])]; tensor var_418_end_mask_0 = const()[name = tensor("op_418_end_mask_0"), val = tensor([true, true, true, true, false])]; tensor var_418_squeeze_mask_0 = const()[name = tensor("op_418_squeeze_mask_0"), val = tensor([false, false, false, false, true])]; tensor var_418 = slice_by_index(begin = var_418_begin_0, end = var_418_end_0, end_mask = var_418_end_mask_0, squeeze_mask = var_418_squeeze_mask_0, x = q_15)[name = tensor("op_418")]; tensor var_420_begin_0 = const()[name = tensor("op_420_begin_0"), val = tensor([0, 0, 0, 0, 0])]; tensor var_420_end_0 = const()[name = tensor("op_420_end_0"), val = tensor([0, 0, 8, 32, 1])]; tensor var_420_end_mask_0 = const()[name = tensor("op_420_end_mask_0"), val = tensor([true, true, true, true, false])]; tensor var_420_squeeze_mask_0 = const()[name = tensor("op_420_squeeze_mask_0"), val = tensor([false, false, false, false, true])]; tensor var_420 = slice_by_index(begin = var_420_begin_0, end = var_420_end_0, end_mask = var_420_end_mask_0, squeeze_mask = var_420_squeeze_mask_0, x = k_13)[name = tensor("op_420")]; tensor var_422_begin_0 = const()[name = tensor("op_422_begin_0"), val = tensor([0, 0, 0, 0, 1])]; tensor var_422_end_0 = const()[name = tensor("op_422_end_0"), val = tensor([0, 0, 8, 32, 2])]; tensor var_422_end_mask_0 = const()[name = tensor("op_422_end_mask_0"), val = tensor([true, true, true, true, false])]; tensor var_422_squeeze_mask_0 = const()[name = tensor("op_422_squeeze_mask_0"), val = tensor([false, false, false, false, true])]; tensor var_422 = slice_by_index(begin = var_422_begin_0, end = var_422_end_0, end_mask = var_422_end_mask_0, squeeze_mask = var_422_squeeze_mask_0, x = k_13)[name = tensor("op_422")]; tensor ts_promoted_dtype_0 = const()[name = tensor("ts_promoted_dtype_0"), val = tensor("fp32")]; tensor ts_promoted = cast(dtype = ts_promoted_dtype_0, x = ts)[name = tensor("cast_32")]; tensor var_424 = mul(x = freqs, y = ts_promoted)[name = tensor("op_424")]; tensor rotr = cos(x = var_424)[name = tensor("rotr")]; tensor roti = sin(x = var_424)[name = tensor("roti")]; tensor var_428 = mul(x = var_416, y = rotr)[name = tensor("op_428")]; tensor var_429 = mul(x = var_418, y = roti)[name = tensor("op_429")]; tensor qor_5 = sub(x = var_428, y = var_429)[name = tensor("qor_5")]; tensor var_431 = mul(x = var_416, y = roti)[name = tensor("op_431")]; tensor var_432 = mul(x = var_418, y = rotr)[name = tensor("op_432")]; tensor qoi_5 = add(x = var_431, y = var_432)[name = tensor("qoi_5")]; tensor var_434 = mul(x = var_420, y = rotr)[name = tensor("op_434")]; tensor var_435 = mul(x = var_422, y = roti)[name = tensor("op_435")]; tensor kor_5 = sub(x = var_434, y = var_435)[name = tensor("kor_5")]; tensor var_437 = mul(x = var_420, y = roti)[name = tensor("op_437")]; tensor var_438 = mul(x = var_422, y = rotr)[name = tensor("op_438")]; tensor koi_5 = add(x = var_437, y = var_438)[name = tensor("koi_5")]; tensor qo_axis_0 = const()[name = tensor("qo_axis_0"), val = tensor(-1)]; tensor qo = stack(axis = qo_axis_0, values = (qor_5, qoi_5))[name = tensor("qo")]; tensor ko_axis_0 = const()[name = tensor("ko_axis_0"), val = tensor(-1)]; tensor ko = stack(axis = ko_axis_0, values = (kor_5, koi_5))[name = tensor("ko")]; tensor concat_11_axis_0 = const()[name = tensor("concat_11_axis_0"), val = tensor(0)]; tensor concat_11_interleave_0 = const()[name = tensor("concat_11_interleave_0"), val = tensor(false)]; tensor concat_11 = concat(axis = concat_11_axis_0, interleave = concat_11_interleave_0, values = (gather_21, gather_22, gather_23, gather_24))[name = tensor("concat_11")]; tensor q_17 = reshape(shape = concat_11, x = qo)[name = tensor("q_17")]; tensor k = reshape(shape = concat_11, x = ko)[name = tensor("k")]; tensor var_455 = const()[name = tensor("op_455"), val = tensor([0, 2, 1, 3])]; tensor var_457 = const()[name = tensor("op_457"), val = tensor([0, 2, 1, 3])]; tensor keys = transpose(perm = var_457, x = k)[name = tensor("transpose_3")]; tensor var_459_shape = shape(x = keys)[name = tensor("op_459_shape")]; tensor gather_26_batch_dims_0 = const()[name = tensor("gather_26_batch_dims_0"), val = tensor(0)]; tensor gather_26_validate_indices_0 = const()[name = tensor("gather_26_validate_indices_0"), val = tensor(false)]; tensor select_15 = const()[name = tensor("select_15"), val = tensor(0)]; tensor gather_26_axis_1 = const()[name = tensor("gather_26_axis_1"), val = tensor(0)]; tensor gather_26 = gather(axis = gather_26_axis_1, batch_dims = gather_26_batch_dims_0, indices = select_15, validate_indices = gather_26_validate_indices_0, x = var_459_shape)[name = tensor("gather_26")]; tensor gather_27_batch_dims_0 = const()[name = tensor("gather_27_batch_dims_0"), val = tensor(0)]; tensor gather_27_validate_indices_0 = const()[name = tensor("gather_27_validate_indices_0"), val = tensor(false)]; tensor select_16 = const()[name = tensor("select_16"), val = tensor(2)]; tensor gather_27_axis_1 = const()[name = tensor("gather_27_axis_1"), val = tensor(0)]; tensor gather_27 = gather(axis = gather_27_axis_1, batch_dims = gather_27_batch_dims_0, indices = select_16, validate_indices = gather_27_validate_indices_0, x = var_459_shape)[name = tensor("gather_27")]; tensor const_20 = const()[name = tensor("const_20"), val = tensor(0)]; tensor const_21 = const()[name = tensor("const_21"), val = tensor(1)]; tensor positions = range_1d(end = gather_27, start = const_20, step = const_21)[name = tensor("positions")]; tensor concat_13_axis_0 = const()[name = tensor("concat_13_axis_0"), val = tensor(0)]; tensor concat_13_interleave_0 = const()[name = tensor("concat_13_interleave_0"), val = tensor(false)]; tensor concat_13 = concat(axis = concat_13_axis_0, interleave = concat_13_interleave_0, values = (gather_26, var_171))[name = tensor("concat_13")]; tensor expand_dims_1_axes_0 = const()[name = tensor("expand_dims_1_axes_0"), val = tensor([0])]; tensor expand_dims_1 = expand_dims(axes = expand_dims_1_axes_0, x = positions)[name = tensor("expand_dims_1")]; tensor shape_1 = shape(x = expand_dims_1)[name = tensor("shape_1")]; tensor equal_1_y_0 = const()[name = tensor("equal_1_y_0"), val = tensor(-1)]; tensor equal_1 = equal(x = concat_13, y = equal_1_y_0)[name = tensor("equal_1")]; tensor select_1 = select(a = shape_1, b = concat_13, cond = equal_1)[name = tensor("select_1")]; tensor real_div_1 = real_div(x = select_1, y = shape_1)[name = tensor("real_div_1")]; tensor pos_k_5 = tile(reps = real_div_1, x = expand_dims_1)[name = tensor("pos_k_5")]; tensor pos_k_axes_0 = const()[name = tensor("pos_k_axes_0"), val = tensor([1])]; tensor pos_k = expand_dims(axes = pos_k_axes_0, x = pos_k_5)[name = tensor("pos_k")]; tensor var_466 = const()[name = tensor("op_466"), val = tensor([-1, 1, 1])]; tensor var_467 = reshape(shape = var_466, x = offset)[name = tensor("op_467")]; tensor const_22 = const()[name = tensor("const_22"), val = tensor(0)]; tensor const_23 = const()[name = tensor("const_23"), val = tensor(1)]; tensor var_468 = range_1d(end = gather_17, start = const_22, step = const_23)[name = tensor("op_468")]; tensor var_469 = const()[name = tensor("op_469"), val = tensor([-1, 1])]; tensor var_470 = reshape(shape = var_469, x = var_468)[name = tensor("op_470")]; tensor pos_q = add(x = var_467, y = var_470)[name = tensor("pos_q")]; tensor delta = sub(x = pos_q, y = pos_k)[name = tensor("delta")]; tensor var_473 = greater_equal(x = pos_k, y = var_163)[name = tensor("op_473")]; tensor var_474 = greater_equal(x = delta, y = var_163)[name = tensor("op_474")]; tensor attn_bias_7 = logical_and(x = var_473, y = var_474)[name = tensor("attn_bias_7")]; tensor var_476 = less(x = delta, y = var_175)[name = tensor("op_476")]; tensor attn_bias_9 = logical_and(x = attn_bias_7, y = var_476)[name = tensor("attn_bias_9")]; tensor attn_bias_axes_0 = const()[name = tensor("attn_bias_axes_0"), val = tensor([1])]; tensor attn_bias = expand_dims(axes = attn_bias_axes_0, x = attn_bias_9)[name = tensor("attn_bias")]; tensor cast_28_dtype_0 = const()[name = tensor("cast_28_dtype_0"), val = tensor("fp32")]; tensor sub_1_x_0 = const()[name = tensor("sub_1_x_0"), val = tensor(0x1p+0)]; tensor cast_28 = cast(dtype = cast_28_dtype_0, x = attn_bias)[name = tensor("cast_31")]; tensor sub_1 = sub(x = sub_1_x_0, y = cast_28)[name = tensor("sub_1")]; tensor mul_2_x_0 = const()[name = tensor("mul_2_x_0"), val = tensor(-0x1.d4cp+14)]; tensor mul_2 = mul(x = mul_2_x_0, y = sub_1)[name = tensor("mul_2")]; tensor mul_3_y_0 = const()[name = tensor("mul_3_y_0"), val = tensor(0x1p-3)]; tensor q = transpose(perm = var_455, x = q_17)[name = tensor("transpose_4")]; tensor mul_3 = mul(x = q, y = mul_3_y_0)[name = tensor("mul_3")]; tensor matmul_1_transpose_y_0 = const()[name = tensor("matmul_1_transpose_y_0"), val = tensor(true)]; tensor matmul_1_transpose_x_0 = const()[name = tensor("matmul_1_transpose_x_0"), val = tensor(false)]; tensor matmul_1 = matmul(transpose_x = matmul_1_transpose_x_0, transpose_y = matmul_1_transpose_y_0, x = mul_3, y = keys)[name = tensor("matmul_1")]; tensor add_1 = add(x = matmul_1, y = mul_2)[name = tensor("add_1")]; tensor softmax_1_axis_0 = const()[name = tensor("softmax_1_axis_0"), val = tensor(-1)]; tensor softmax_1 = softmax(axis = softmax_1_axis_0, x = add_1)[name = tensor("softmax_1")]; tensor x_19_transpose_x_0 = const()[name = tensor("x_19_transpose_x_0"), val = tensor(false)]; tensor x_19_transpose_y_0 = const()[name = tensor("x_19_transpose_y_0"), val = tensor(false)]; tensor x_19 = matmul(transpose_x = x_19_transpose_x_0, transpose_y = x_19_transpose_y_0, x = softmax_1, y = squeeze_5)[name = tensor("x_19")]; tensor var_481_shape = shape(x = x_19)[name = tensor("op_481_shape")]; tensor gather_28_batch_dims_0 = const()[name = tensor("gather_28_batch_dims_0"), val = tensor(0)]; tensor gather_28_validate_indices_0 = const()[name = tensor("gather_28_validate_indices_0"), val = tensor(false)]; tensor select_17 = const()[name = tensor("select_17"), val = tensor(0)]; tensor gather_28_axis_1 = const()[name = tensor("gather_28_axis_1"), val = tensor(0)]; tensor gather_28 = gather(axis = gather_28_axis_1, batch_dims = gather_28_batch_dims_0, indices = select_17, validate_indices = gather_28_validate_indices_0, x = var_481_shape)[name = tensor("gather_28")]; tensor gather_30_batch_dims_0 = const()[name = tensor("gather_30_batch_dims_0"), val = tensor(0)]; tensor gather_30_validate_indices_0 = const()[name = tensor("gather_30_validate_indices_0"), val = tensor(false)]; tensor select_18 = const()[name = tensor("select_18"), val = tensor(2)]; tensor gather_30_axis_1 = const()[name = tensor("gather_30_axis_1"), val = tensor(0)]; tensor gather_30 = gather(axis = gather_30_axis_1, batch_dims = gather_30_batch_dims_0, indices = select_18, validate_indices = gather_30_validate_indices_0, x = var_481_shape)[name = tensor("gather_30")]; tensor var_498 = const()[name = tensor("op_498"), val = tensor(512)]; tensor var_499 = const()[name = tensor("op_499"), val = tensor([0, 2, 1, 3])]; tensor concat_14_axis_0 = const()[name = tensor("concat_14_axis_0"), val = tensor(0)]; tensor concat_14_interleave_0 = const()[name = tensor("concat_14_interleave_0"), val = tensor(false)]; tensor concat_14 = concat(axis = concat_14_axis_0, interleave = concat_14_interleave_0, values = (gather_28, gather_30, var_498))[name = tensor("concat_14")]; tensor x_21 = transpose(perm = var_499, x = x_19)[name = tensor("transpose_2")]; tensor input_69 = reshape(shape = concat_14, x = x_21)[name = tensor("input_69")]; tensor x_23 = linear(bias = linear_1_bias_0, weight = encoder_transformer_transformer_layers_1_self_attn_out_proj_weight, x = input_69)[name = tensor("linear_5")]; tensor var_507 = mul(x = encoder_transformer_transformer_layers_1_layer_scale_1_scale, y = x_23)[name = tensor("op_507")]; tensor input_71 = add(x = input_67, y = var_507)[name = tensor("input_71")]; tensor input_73_axes_0 = const()[name = tensor("input_73_axes_0"), val = tensor([-1])]; tensor input_73 = layer_norm(axes = input_73_axes_0, beta = encoder_transformer_transformer_layers_1_norm2_bias, epsilon = var_178, gamma = encoder_transformer_transformer_layers_1_norm2_weight, x = input_71)[name = tensor("input_73")]; tensor var_514 = linear(bias = linear_2_bias_0, weight = encoder_transformer_transformer_layers_1_linear1_weight, x = input_73)[name = tensor("linear_6")]; tensor input_75_mode_0 = const()[name = tensor("input_75_mode_0"), val = tensor("EXACT")]; tensor input_75 = gelu(mode = input_75_mode_0, x = var_514)[name = tensor("input_75")]; tensor x_25 = linear(bias = linear_1_bias_0, weight = encoder_transformer_transformer_layers_1_linear2_weight, x = input_75)[name = tensor("linear_7")]; tensor var_520 = mul(x = encoder_transformer_transformer_layers_1_layer_scale_2_scale, y = x_25)[name = tensor("op_520")]; tensor z = add(x = input_71, y = var_520)[name = tensor("z")]; tensor x_perm_0 = const()[name = tensor("x_perm_0"), val = tensor([0, 2, 1])]; tensor var_526 = const()[name = tensor("op_526"), val = tensor(-1)]; tensor var_533_begin_0 = const()[name = tensor("op_533_begin_0"), val = tensor([0, 0, 0])]; tensor var_533_end_0 = const()[name = tensor("op_533_end_0"), val = tensor([0, 512, 1])]; tensor var_533_end_mask_0 = const()[name = tensor("op_533_end_mask_0"), val = tensor([true, true, false])]; tensor x = transpose(perm = x_perm_0, x = z)[name = tensor("transpose_1")]; tensor var_533 = slice_by_index(begin = var_533_begin_0, end = var_533_end_0, end_mask = var_533_end_mask_0, x = x)[name = tensor("op_533")]; tensor concat_15 = const()[name = tensor("concat_15"), val = tensor([-1, -1, 16])]; tensor shape_2 = shape(x = var_533)[name = tensor("shape_2")]; tensor equal_2 = const()[name = tensor("equal_2"), val = tensor([true, true, false])]; tensor select_2 = select(a = shape_2, b = concat_15, cond = equal_2)[name = tensor("select_2")]; tensor real_div_2 = real_div(x = select_2, y = shape_2)[name = tensor("real_div_2")]; tensor init = tile(reps = real_div_2, x = var_533)[name = tensor("init")]; tensor input_interleave_0 = const()[name = tensor("input_interleave_0"), val = tensor(false)]; tensor input = concat(axis = var_526, interleave = input_interleave_0, values = (init, x))[name = tensor("input")]; tensor emb_pad_type_0 = const()[name = tensor("emb_pad_type_0"), val = tensor("valid")]; tensor emb_strides_0 = const()[name = tensor("emb_strides_0"), val = tensor([16])]; tensor emb_pad_0 = const()[name = tensor("emb_pad_0"), val = tensor([0, 0])]; tensor emb_dilations_0 = const()[name = tensor("emb_dilations_0"), val = tensor([1])]; tensor emb_groups_0 = const()[name = tensor("emb_groups_0"), val = tensor(1)]; tensor emb = conv(dilations = emb_dilations_0, groups = emb_groups_0, pad = emb_pad_0, pad_type = emb_pad_type_0, strides = emb_strides_0, weight = downsample_conv_conv_weight, x = input)[name = tensor("emb")]; tensor var_546_perm_0 = const()[name = tensor("op_546_perm_0"), val = tensor([0, -1, -2])]; tensor linear_8_bias_0 = const()[name = tensor("linear_8_bias_0"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72570368)))]; tensor var_546 = transpose(perm = var_546_perm_0, x = emb)[name = tensor("transpose_0")]; tensor conditioning = linear(bias = linear_8_bias_0, weight = speaker_proj_weight, x = var_546)[name = tensor("linear_8")]; } -> (conditioning); }