program(1.3) [buildInfo = dict({{"coremlc-component-MIL", "3404.14.1"}, {"coremlc-version", "3404.16.1"}, {"coremltools-component-torch", "2.3.1"}, {"coremltools-version", "7.1.4"}}), mldb_token = string("mldb-nwypm2py9o")] { func main(tensor audio, state> cast_27_state, state> input_17_cast_fp16_state, state> input_27_cast_fp16_state, state> input_37_cast_fp16_state, state> input_47_cast_fp16_state, state> input_4_cast_fp16_state, state> input_7_cast_fp16_state) [BNNSOptions = dict({{"StateMode", "Streaming"}}), UserMetadata = dict({{"iteration", "2679528"}, {"taskid", "39akp89edc"}})] { int32 var_11 = const()[name = string("op_11"), val = int32(1)]; tensor var_15 = const()[name = string("op_15"), val = tensor([80])]; tensor var_17 = const()[name = string("op_17"), val = tensor([1])]; string input0_1_pad_type_0 = const()[name = string("input0_1_pad_type_0"), val = string("custom")]; tensor input0_1_pad_0 = const()[name = string("input0_1_pad_0"), val = tensor([80, 80])]; string audio_to_fp16_dtype_0 = const()[name = string("audio_to_fp16_dtype_0"), val = string("fp16")]; tensor front_end_0_weight_to_fp16 = const()[name = string("front_end_0_weight_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(64)))]; tensor cast_27 = cast(dtype = audio_to_fp16_dtype_0, x = audio)[name = string("cast_27")]; tensor cast_27_state_input = read_state(input = cast_27_state); tensor cast_27_state_updated = slice_update(begin = tensor([0, 0, 80]), end = tensor([1, 1, 400]), end_mask = tensor([false, false, false]), update = cast_27, x = cast_27_state_input); tensor input0_1_cast_fp16 = conv(dilations = var_17, groups = var_11, pad = tensor([0, 0]), pad_type = input0_1_pad_type_0, strides = var_15, weight = front_end_0_weight_to_fp16, x = cast_27_state_updated); write_state(data = cast_27_state_updated, input = cast_27_state); tensor var_20_cast_fp16 = relu(x = input0_1_cast_fp16)[name = string("op_20_cast_fp16")]; bool var_22 = const()[name = string("op_22"), val = bool(true)]; tensor var_27 = const()[name = string("op_27"), val = tensor([1])]; tensor mean_y_4_cast_fp16 = reduce_mean(axes = var_27, keep_dims = var_22, x = var_20_cast_fp16)[name = string("mean_y_4_cast_fp16")]; tensor var_29_cast_fp16 = sub(x = var_20_cast_fp16, y = mean_y_4_cast_fp16)[name = string("op_29_cast_fp16")]; tensor var_30_cast_fp16 = square(x = var_29_cast_fp16); tensor var_31 = const()[name = string("op_31"), val = tensor([1])]; tensor var_32_cast_fp16 = reduce_mean(axes = var_31, keep_dims = var_22, x = var_30_cast_fp16)[name = string("op_32_cast_fp16")]; fp16 var_33_to_fp16 = const()[name = string("op_33_to_fp16"), val = fp16(0x1p-14)]; tensor var_34_cast_fp16 = add(x = var_32_cast_fp16, y = var_33_to_fp16)[name = string("op_34_cast_fp16")]; tensor std_y_4_cast_fp16 = sqrt(x = var_34_cast_fp16)[name = string("std_y_4_cast_fp16")]; tensor front_norm_norm_gamma_to_fp16 = const()[name = string("front_norm_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(82048)))]; tensor var_37_cast_fp16 = mul(x = front_norm_norm_gamma_to_fp16, y = var_29_cast_fp16)[name = string("op_37_cast_fp16")]; tensor var_38_cast_fp16 = real_div(x = var_37_cast_fp16, y = std_y_4_cast_fp16)[name = string("op_38_cast_fp16")]; tensor front_norm_norm_beta_to_fp16 = const()[name = string("front_norm_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(82624)))]; tensor input_55_cast_fp16 = add(x = var_38_cast_fp16, y = front_norm_norm_beta_to_fp16)[name = string("input_55_cast_fp16")]; int32 var_41 = const()[name = string("op_41"), val = int32(1)]; tensor var_46 = const()[name = string("op_46"), val = tensor([1])]; tensor var_48 = const()[name = string("op_48"), val = tensor([1])]; string input_57_pad_type_0 = const()[name = string("input_57_pad_type_0"), val = string("custom")]; tensor input_57_pad_0 = const()[name = string("input_57_pad_0"), val = tensor([0, 0])]; tensor to_latent_weight_to_fp16 = const()[name = string("to_latent_weight_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(83200)))]; tensor input_57_cast_fp16 = conv(dilations = var_48, groups = var_41, pad = input_57_pad_0, pad_type = input_57_pad_type_0, strides = var_46, weight = to_latent_weight_to_fp16, x = input_55_cast_fp16)[name = string("input_57_cast_fp16")]; int32 var_56 = const()[name = string("op_56"), val = int32(1)]; int32 var_57 = const()[name = string("op_57"), val = int32(128)]; bool var_61 = const()[name = string("op_61"), val = bool(true)]; tensor var_79 = const()[name = string("op_79"), val = tensor([1])]; tensor var_81 = const()[name = string("op_81"), val = tensor([1])]; string input_5_pad_type_0 = const()[name = string("input_5_pad_type_0"), val = string("custom")]; tensor input_5_pad_0 = const()[name = string("input_5_pad_0"), val = tensor([0, 0])]; tensor sep_module_0_tcn_0_weight_to_fp16 = const()[name = string("sep_module_0_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(148800)))]; tensor input_5_cast_fp16 = conv(dilations = var_81, groups = var_56, pad = input_5_pad_0, pad_type = input_5_pad_type_0, strides = var_79, weight = sep_module_0_tcn_0_weight_to_fp16, x = input_57_cast_fp16)[name = string("input_5_cast_fp16")]; fp32 var_85_alpha_1 = const()[name = string("op_85_alpha_1"), val = fp32(0x1.07b3fap-2)]; tensor var_85_cast_fp16 = leaky_relu(alpha = fp16(0x1.07cp-2), x = input_5_cast_fp16); tensor var_89 = const()[name = string("op_89"), val = tensor([1])]; tensor mean_y_3_cast_fp16 = reduce_mean(axes = var_89, keep_dims = var_61, x = var_85_cast_fp16)[name = string("mean_y_3_cast_fp16")]; tensor var_91_cast_fp16 = sub(x = var_85_cast_fp16, y = mean_y_3_cast_fp16)[name = string("op_91_cast_fp16")]; tensor var_92_cast_fp16 = square(x = var_91_cast_fp16); tensor var_93 = const()[name = string("op_93"), val = tensor([1])]; tensor var_94_cast_fp16 = reduce_mean(axes = var_93, keep_dims = var_61, x = var_92_cast_fp16)[name = string("op_94_cast_fp16")]; fp16 var_95_to_fp16 = const()[name = string("op_95_to_fp16"), val = fp16(0x1p-14)]; tensor var_96_cast_fp16 = add(x = var_94_cast_fp16, y = var_95_to_fp16)[name = string("op_96_cast_fp16")]; tensor std_y_3_cast_fp16 = sqrt(x = var_96_cast_fp16)[name = string("std_y_3_cast_fp16")]; tensor sep_module_0_tcn_2_norm_gamma_to_fp16 = const()[name = string("sep_module_0_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(181632)))]; tensor var_99_cast_fp16 = mul(x = sep_module_0_tcn_2_norm_gamma_to_fp16, y = var_91_cast_fp16)[name = string("op_99_cast_fp16")]; tensor var_100_cast_fp16 = real_div(x = var_99_cast_fp16, y = std_y_3_cast_fp16)[name = string("op_100_cast_fp16")]; tensor sep_module_0_tcn_2_norm_beta_to_fp16 = const()[name = string("sep_module_0_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(181952)))]; tensor input_7_cast_fp16 = add(x = var_100_cast_fp16, y = sep_module_0_tcn_2_norm_beta_to_fp16)[name = string("input_7_cast_fp16")]; tensor input_9_pad_0 = const()[name = string("input_9_pad_0"), val = tensor([0, 0, 0, 0, 2, 0])]; string input_9_mode_0 = const()[name = string("input_9_mode_0"), val = string("constant")]; fp16 const_0_to_fp16 = const()[name = string("const_0_to_fp16"), val = fp16(0x0p+0)]; tensor input_7_cast_fp16_state_input = read_state(input = input_7_cast_fp16_state); tensor input_9_cast_fp16 = slice_update(begin = tensor([0, 0, 2]), end = tensor([1, 128, 6]), end_mask = tensor([false, false, false]), update = input_7_cast_fp16, x = input_7_cast_fp16_state_input); write_state(data = input_9_cast_fp16, input = input_7_cast_fp16_state); tensor var_105 = const()[name = string("op_105"), val = tensor([1])]; tensor var_107 = const()[name = string("op_107"), val = tensor([1])]; string input_11_pad_type_0 = const()[name = string("input_11_pad_type_0"), val = string("custom")]; tensor input_11_pad_0 = const()[name = string("input_11_pad_0"), val = tensor([0, 0])]; tensor sep_module_0_tcn_4_weight_to_fp16 = const()[name = string("sep_module_0_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(182272)))]; tensor input_11_cast_fp16 = conv(dilations = var_107, groups = var_57, pad = input_11_pad_0, pad_type = input_11_pad_type_0, strides = var_105, weight = sep_module_0_tcn_4_weight_to_fp16, x = input_9_cast_fp16)[name = string("input_11_cast_fp16")]; fp32 var_111_alpha_1 = const()[name = string("op_111_alpha_1"), val = fp32(-0x1.388ed6p-8)]; tensor var_111_cast_fp16 = leaky_relu(alpha = fp16(-0x1.388p-8), x = input_11_cast_fp16); tensor var_115 = const()[name = string("op_115"), val = tensor([1])]; tensor mean_y_5_cast_fp16 = reduce_mean(axes = var_115, keep_dims = var_61, x = var_111_cast_fp16)[name = string("mean_y_5_cast_fp16")]; tensor var_117_cast_fp16 = sub(x = var_111_cast_fp16, y = mean_y_5_cast_fp16)[name = string("op_117_cast_fp16")]; tensor var_118_cast_fp16 = square(x = var_117_cast_fp16); tensor var_119 = const()[name = string("op_119"), val = tensor([1])]; tensor var_120_cast_fp16 = reduce_mean(axes = var_119, keep_dims = var_61, x = var_118_cast_fp16)[name = string("op_120_cast_fp16")]; fp16 var_121_to_fp16 = const()[name = string("op_121_to_fp16"), val = fp16(0x1p-14)]; tensor var_122_cast_fp16 = add(x = var_120_cast_fp16, y = var_121_to_fp16)[name = string("op_122_cast_fp16")]; tensor std_y_5_cast_fp16 = sqrt(x = var_122_cast_fp16)[name = string("std_y_5_cast_fp16")]; tensor sep_module_0_tcn_6_norm_gamma_to_fp16 = const()[name = string("sep_module_0_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(183104)))]; tensor var_125_cast_fp16 = mul(x = sep_module_0_tcn_6_norm_gamma_to_fp16, y = var_117_cast_fp16)[name = string("op_125_cast_fp16")]; tensor var_126_cast_fp16 = real_div(x = var_125_cast_fp16, y = std_y_5_cast_fp16)[name = string("op_126_cast_fp16")]; tensor sep_module_0_tcn_6_norm_beta_to_fp16 = const()[name = string("sep_module_0_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(183424)))]; tensor y_2_cast_fp16 = add(x = var_126_cast_fp16, y = sep_module_0_tcn_6_norm_beta_to_fp16)[name = string("y_2_cast_fp16")]; tensor input_13_cast_fp16 = add(x = input_57_cast_fp16, y = y_2_cast_fp16)[name = string("input_13_cast_fp16")]; tensor var_137 = const()[name = string("op_137"), val = tensor([1])]; tensor var_139 = const()[name = string("op_139"), val = tensor([1])]; string input_15_pad_type_0 = const()[name = string("input_15_pad_type_0"), val = string("custom")]; tensor input_15_pad_0 = const()[name = string("input_15_pad_0"), val = tensor([0, 0])]; tensor sep_module_1_tcn_0_weight_to_fp16 = const()[name = string("sep_module_1_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(183744)))]; tensor input_15_cast_fp16 = conv(dilations = var_139, groups = var_56, pad = input_15_pad_0, pad_type = input_15_pad_type_0, strides = var_137, weight = sep_module_1_tcn_0_weight_to_fp16, x = input_13_cast_fp16)[name = string("input_15_cast_fp16")]; fp32 var_143_alpha_1 = const()[name = string("op_143_alpha_1"), val = fp32(0x1.cc1cd6p-2)]; tensor var_143_cast_fp16 = leaky_relu(alpha = fp16(0x1.ccp-2), x = input_15_cast_fp16); tensor var_147 = const()[name = string("op_147"), val = tensor([1])]; tensor mean_y_7_cast_fp16 = reduce_mean(axes = var_147, keep_dims = var_61, x = var_143_cast_fp16)[name = string("mean_y_7_cast_fp16")]; tensor var_149_cast_fp16 = sub(x = var_143_cast_fp16, y = mean_y_7_cast_fp16)[name = string("op_149_cast_fp16")]; tensor var_150_cast_fp16 = square(x = var_149_cast_fp16); tensor var_151 = const()[name = string("op_151"), val = tensor([1])]; tensor var_152_cast_fp16 = reduce_mean(axes = var_151, keep_dims = var_61, x = var_150_cast_fp16)[name = string("op_152_cast_fp16")]; fp16 var_153_to_fp16 = const()[name = string("op_153_to_fp16"), val = fp16(0x1p-14)]; tensor var_154_cast_fp16 = add(x = var_152_cast_fp16, y = var_153_to_fp16)[name = string("op_154_cast_fp16")]; tensor std_y_7_cast_fp16 = sqrt(x = var_154_cast_fp16)[name = string("std_y_7_cast_fp16")]; tensor sep_module_1_tcn_2_norm_gamma_to_fp16 = const()[name = string("sep_module_1_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(216576)))]; tensor var_157_cast_fp16 = mul(x = sep_module_1_tcn_2_norm_gamma_to_fp16, y = var_149_cast_fp16)[name = string("op_157_cast_fp16")]; tensor var_158_cast_fp16 = real_div(x = var_157_cast_fp16, y = std_y_7_cast_fp16)[name = string("op_158_cast_fp16")]; tensor sep_module_1_tcn_2_norm_beta_to_fp16 = const()[name = string("sep_module_1_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(216896)))]; tensor input_17_cast_fp16 = add(x = var_158_cast_fp16, y = sep_module_1_tcn_2_norm_beta_to_fp16)[name = string("input_17_cast_fp16")]; tensor input_19_pad_0 = const()[name = string("input_19_pad_0"), val = tensor([0, 0, 0, 0, 4, 0])]; string input_19_mode_0 = const()[name = string("input_19_mode_0"), val = string("constant")]; fp16 const_1_to_fp16 = const()[name = string("const_1_to_fp16"), val = fp16(0x0p+0)]; tensor input_17_cast_fp16_state_input = read_state(input = input_17_cast_fp16_state); tensor input_19_cast_fp16 = slice_update(begin = tensor([0, 0, 4]), end = tensor([1, 128, 8]), end_mask = tensor([false, false, false]), update = input_17_cast_fp16, x = input_17_cast_fp16_state_input); write_state(data = input_19_cast_fp16, input = input_17_cast_fp16_state); tensor var_163 = const()[name = string("op_163"), val = tensor([1])]; tensor var_165 = const()[name = string("op_165"), val = tensor([2])]; string input_21_pad_type_0 = const()[name = string("input_21_pad_type_0"), val = string("custom")]; tensor input_21_pad_0 = const()[name = string("input_21_pad_0"), val = tensor([0, 0])]; tensor sep_module_1_tcn_4_weight_to_fp16 = const()[name = string("sep_module_1_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(217216)))]; tensor input_21_cast_fp16 = conv(dilations = var_165, groups = var_57, pad = input_21_pad_0, pad_type = input_21_pad_type_0, strides = var_163, weight = sep_module_1_tcn_4_weight_to_fp16, x = input_19_cast_fp16)[name = string("input_21_cast_fp16")]; fp32 var_169_alpha_1 = const()[name = string("op_169_alpha_1"), val = fp32(-0x1.80e57p-2)]; tensor var_169_cast_fp16 = leaky_relu(alpha = fp16(-0x1.81p-2), x = input_21_cast_fp16); tensor var_173 = const()[name = string("op_173"), val = tensor([1])]; tensor mean_y_9_cast_fp16 = reduce_mean(axes = var_173, keep_dims = var_61, x = var_169_cast_fp16)[name = string("mean_y_9_cast_fp16")]; tensor var_175_cast_fp16 = sub(x = var_169_cast_fp16, y = mean_y_9_cast_fp16)[name = string("op_175_cast_fp16")]; tensor var_176_cast_fp16 = square(x = var_175_cast_fp16); tensor var_177 = const()[name = string("op_177"), val = tensor([1])]; tensor var_178_cast_fp16 = reduce_mean(axes = var_177, keep_dims = var_61, x = var_176_cast_fp16)[name = string("op_178_cast_fp16")]; fp16 var_179_to_fp16 = const()[name = string("op_179_to_fp16"), val = fp16(0x1p-14)]; tensor var_180_cast_fp16 = add(x = var_178_cast_fp16, y = var_179_to_fp16)[name = string("op_180_cast_fp16")]; tensor std_y_9_cast_fp16 = sqrt(x = var_180_cast_fp16)[name = string("std_y_9_cast_fp16")]; tensor sep_module_1_tcn_6_norm_gamma_to_fp16 = const()[name = string("sep_module_1_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(218048)))]; tensor var_183_cast_fp16 = mul(x = sep_module_1_tcn_6_norm_gamma_to_fp16, y = var_175_cast_fp16)[name = string("op_183_cast_fp16")]; tensor var_184_cast_fp16 = real_div(x = var_183_cast_fp16, y = std_y_9_cast_fp16)[name = string("op_184_cast_fp16")]; tensor sep_module_1_tcn_6_norm_beta_to_fp16 = const()[name = string("sep_module_1_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(218368)))]; tensor y_4_cast_fp16 = add(x = var_184_cast_fp16, y = sep_module_1_tcn_6_norm_beta_to_fp16)[name = string("y_4_cast_fp16")]; tensor input_23_cast_fp16 = add(x = input_13_cast_fp16, y = y_4_cast_fp16)[name = string("input_23_cast_fp16")]; tensor var_195 = const()[name = string("op_195"), val = tensor([1])]; tensor var_197 = const()[name = string("op_197"), val = tensor([1])]; string input_25_pad_type_0 = const()[name = string("input_25_pad_type_0"), val = string("custom")]; tensor input_25_pad_0 = const()[name = string("input_25_pad_0"), val = tensor([0, 0])]; tensor sep_module_2_tcn_0_weight_to_fp16 = const()[name = string("sep_module_2_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(218688)))]; tensor input_25_cast_fp16 = conv(dilations = var_197, groups = var_56, pad = input_25_pad_0, pad_type = input_25_pad_type_0, strides = var_195, weight = sep_module_2_tcn_0_weight_to_fp16, x = input_23_cast_fp16)[name = string("input_25_cast_fp16")]; fp32 var_201_alpha_1 = const()[name = string("op_201_alpha_1"), val = fp32(0x1.6bd2fcp-2)]; tensor var_201_cast_fp16 = leaky_relu(alpha = fp16(0x1.6bcp-2), x = input_25_cast_fp16); tensor var_205 = const()[name = string("op_205"), val = tensor([1])]; tensor mean_y_11_cast_fp16 = reduce_mean(axes = var_205, keep_dims = var_61, x = var_201_cast_fp16)[name = string("mean_y_11_cast_fp16")]; tensor var_207_cast_fp16 = sub(x = var_201_cast_fp16, y = mean_y_11_cast_fp16)[name = string("op_207_cast_fp16")]; tensor var_208_cast_fp16 = square(x = var_207_cast_fp16); tensor var_209 = const()[name = string("op_209"), val = tensor([1])]; tensor var_210_cast_fp16 = reduce_mean(axes = var_209, keep_dims = var_61, x = var_208_cast_fp16)[name = string("op_210_cast_fp16")]; fp16 var_211_to_fp16 = const()[name = string("op_211_to_fp16"), val = fp16(0x1p-14)]; tensor var_212_cast_fp16 = add(x = var_210_cast_fp16, y = var_211_to_fp16)[name = string("op_212_cast_fp16")]; tensor std_y_11_cast_fp16 = sqrt(x = var_212_cast_fp16)[name = string("std_y_11_cast_fp16")]; tensor sep_module_2_tcn_2_norm_gamma_to_fp16 = const()[name = string("sep_module_2_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(251520)))]; tensor var_215_cast_fp16 = mul(x = sep_module_2_tcn_2_norm_gamma_to_fp16, y = var_207_cast_fp16)[name = string("op_215_cast_fp16")]; tensor var_216_cast_fp16 = real_div(x = var_215_cast_fp16, y = std_y_11_cast_fp16)[name = string("op_216_cast_fp16")]; tensor sep_module_2_tcn_2_norm_beta_to_fp16 = const()[name = string("sep_module_2_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(251840)))]; tensor input_27_cast_fp16 = add(x = var_216_cast_fp16, y = sep_module_2_tcn_2_norm_beta_to_fp16)[name = string("input_27_cast_fp16")]; tensor input_29_pad_0 = const()[name = string("input_29_pad_0"), val = tensor([0, 0, 0, 0, 8, 0])]; string input_29_mode_0 = const()[name = string("input_29_mode_0"), val = string("constant")]; fp16 const_2_to_fp16 = const()[name = string("const_2_to_fp16"), val = fp16(0x0p+0)]; tensor input_27_cast_fp16_state_input = read_state(input = input_27_cast_fp16_state); tensor input_29_cast_fp16 = slice_update(begin = tensor([0, 0, 8]), end = tensor([1, 128, 12]), end_mask = tensor([false, false, false]), update = input_27_cast_fp16, x = input_27_cast_fp16_state_input); write_state(data = input_29_cast_fp16, input = input_27_cast_fp16_state); tensor var_221 = const()[name = string("op_221"), val = tensor([1])]; tensor var_223 = const()[name = string("op_223"), val = tensor([4])]; string input_31_pad_type_0 = const()[name = string("input_31_pad_type_0"), val = string("custom")]; tensor input_31_pad_0 = const()[name = string("input_31_pad_0"), val = tensor([0, 0])]; tensor sep_module_2_tcn_4_weight_to_fp16 = const()[name = string("sep_module_2_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(252160)))]; tensor input_31_cast_fp16 = conv(dilations = var_223, groups = var_57, pad = input_31_pad_0, pad_type = input_31_pad_type_0, strides = var_221, weight = sep_module_2_tcn_4_weight_to_fp16, x = input_29_cast_fp16)[name = string("input_31_cast_fp16")]; fp32 var_227_alpha_1 = const()[name = string("op_227_alpha_1"), val = fp32(-0x1.10086ep-3)]; tensor var_227_cast_fp16 = leaky_relu(alpha = fp16(-0x1.1p-3), x = input_31_cast_fp16); tensor var_231 = const()[name = string("op_231"), val = tensor([1])]; tensor mean_y_13_cast_fp16 = reduce_mean(axes = var_231, keep_dims = var_61, x = var_227_cast_fp16)[name = string("mean_y_13_cast_fp16")]; tensor var_233_cast_fp16 = sub(x = var_227_cast_fp16, y = mean_y_13_cast_fp16)[name = string("op_233_cast_fp16")]; tensor var_234_cast_fp16 = square(x = var_233_cast_fp16); tensor var_235 = const()[name = string("op_235"), val = tensor([1])]; tensor var_236_cast_fp16 = reduce_mean(axes = var_235, keep_dims = var_61, x = var_234_cast_fp16)[name = string("op_236_cast_fp16")]; fp16 var_237_to_fp16 = const()[name = string("op_237_to_fp16"), val = fp16(0x1p-14)]; tensor var_238_cast_fp16 = add(x = var_236_cast_fp16, y = var_237_to_fp16)[name = string("op_238_cast_fp16")]; tensor std_y_13_cast_fp16 = sqrt(x = var_238_cast_fp16)[name = string("std_y_13_cast_fp16")]; tensor sep_module_2_tcn_6_norm_gamma_to_fp16 = const()[name = string("sep_module_2_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(252992)))]; tensor var_241_cast_fp16 = mul(x = sep_module_2_tcn_6_norm_gamma_to_fp16, y = var_233_cast_fp16)[name = string("op_241_cast_fp16")]; tensor var_242_cast_fp16 = real_div(x = var_241_cast_fp16, y = std_y_13_cast_fp16)[name = string("op_242_cast_fp16")]; tensor sep_module_2_tcn_6_norm_beta_to_fp16 = const()[name = string("sep_module_2_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(253312)))]; tensor y_6_cast_fp16 = add(x = var_242_cast_fp16, y = sep_module_2_tcn_6_norm_beta_to_fp16)[name = string("y_6_cast_fp16")]; tensor input_33_cast_fp16 = add(x = input_23_cast_fp16, y = y_6_cast_fp16)[name = string("input_33_cast_fp16")]; tensor var_253 = const()[name = string("op_253"), val = tensor([1])]; tensor var_255 = const()[name = string("op_255"), val = tensor([1])]; string input_35_pad_type_0 = const()[name = string("input_35_pad_type_0"), val = string("custom")]; tensor input_35_pad_0 = const()[name = string("input_35_pad_0"), val = tensor([0, 0])]; tensor sep_module_3_tcn_0_weight_to_fp16 = const()[name = string("sep_module_3_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(253632)))]; tensor input_35_cast_fp16 = conv(dilations = var_255, groups = var_56, pad = input_35_pad_0, pad_type = input_35_pad_type_0, strides = var_253, weight = sep_module_3_tcn_0_weight_to_fp16, x = input_33_cast_fp16)[name = string("input_35_cast_fp16")]; fp32 var_259_alpha_1 = const()[name = string("op_259_alpha_1"), val = fp32(0x1.c76c66p-2)]; tensor var_259_cast_fp16 = leaky_relu(alpha = fp16(0x1.c78p-2), x = input_35_cast_fp16); tensor var_263 = const()[name = string("op_263"), val = tensor([1])]; tensor mean_y_15_cast_fp16 = reduce_mean(axes = var_263, keep_dims = var_61, x = var_259_cast_fp16)[name = string("mean_y_15_cast_fp16")]; tensor var_265_cast_fp16 = sub(x = var_259_cast_fp16, y = mean_y_15_cast_fp16)[name = string("op_265_cast_fp16")]; tensor var_266_cast_fp16 = square(x = var_265_cast_fp16); tensor var_267 = const()[name = string("op_267"), val = tensor([1])]; tensor var_268_cast_fp16 = reduce_mean(axes = var_267, keep_dims = var_61, x = var_266_cast_fp16)[name = string("op_268_cast_fp16")]; fp16 var_269_to_fp16 = const()[name = string("op_269_to_fp16"), val = fp16(0x1p-14)]; tensor var_270_cast_fp16 = add(x = var_268_cast_fp16, y = var_269_to_fp16)[name = string("op_270_cast_fp16")]; tensor std_y_15_cast_fp16 = sqrt(x = var_270_cast_fp16)[name = string("std_y_15_cast_fp16")]; tensor sep_module_3_tcn_2_norm_gamma_to_fp16 = const()[name = string("sep_module_3_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(286464)))]; tensor var_273_cast_fp16 = mul(x = sep_module_3_tcn_2_norm_gamma_to_fp16, y = var_265_cast_fp16)[name = string("op_273_cast_fp16")]; tensor var_274_cast_fp16 = real_div(x = var_273_cast_fp16, y = std_y_15_cast_fp16)[name = string("op_274_cast_fp16")]; tensor sep_module_3_tcn_2_norm_beta_to_fp16 = const()[name = string("sep_module_3_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(286784)))]; tensor input_37_cast_fp16 = add(x = var_274_cast_fp16, y = sep_module_3_tcn_2_norm_beta_to_fp16)[name = string("input_37_cast_fp16")]; tensor input_39_pad_0 = const()[name = string("input_39_pad_0"), val = tensor([0, 0, 0, 0, 16, 0])]; string input_39_mode_0 = const()[name = string("input_39_mode_0"), val = string("constant")]; fp16 const_3_to_fp16 = const()[name = string("const_3_to_fp16"), val = fp16(0x0p+0)]; tensor input_37_cast_fp16_state_input = read_state(input = input_37_cast_fp16_state); tensor input_39_cast_fp16 = slice_update(begin = tensor([0, 0, 16]), end = tensor([1, 128, 20]), end_mask = tensor([false, false, false]), update = input_37_cast_fp16, x = input_37_cast_fp16_state_input); write_state(data = input_39_cast_fp16, input = input_37_cast_fp16_state); tensor var_279 = const()[name = string("op_279"), val = tensor([1])]; tensor var_281 = const()[name = string("op_281"), val = tensor([8])]; string input_41_pad_type_0 = const()[name = string("input_41_pad_type_0"), val = string("custom")]; tensor input_41_pad_0 = const()[name = string("input_41_pad_0"), val = tensor([0, 0])]; tensor sep_module_3_tcn_4_weight_to_fp16 = const()[name = string("sep_module_3_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(287104)))]; tensor input_41_cast_fp16 = conv(dilations = var_281, groups = var_57, pad = input_41_pad_0, pad_type = input_41_pad_type_0, strides = var_279, weight = sep_module_3_tcn_4_weight_to_fp16, x = input_39_cast_fp16)[name = string("input_41_cast_fp16")]; fp32 var_285_alpha_1 = const()[name = string("op_285_alpha_1"), val = fp32(-0x1.509cf2p-3)]; tensor var_285_cast_fp16 = leaky_relu(alpha = fp16(-0x1.508p-3), x = input_41_cast_fp16); tensor var_289 = const()[name = string("op_289"), val = tensor([1])]; tensor mean_y_17_cast_fp16 = reduce_mean(axes = var_289, keep_dims = var_61, x = var_285_cast_fp16)[name = string("mean_y_17_cast_fp16")]; tensor var_291_cast_fp16 = sub(x = var_285_cast_fp16, y = mean_y_17_cast_fp16)[name = string("op_291_cast_fp16")]; tensor var_292_cast_fp16 = square(x = var_291_cast_fp16); tensor var_293 = const()[name = string("op_293"), val = tensor([1])]; tensor var_294_cast_fp16 = reduce_mean(axes = var_293, keep_dims = var_61, x = var_292_cast_fp16)[name = string("op_294_cast_fp16")]; fp16 var_295_to_fp16 = const()[name = string("op_295_to_fp16"), val = fp16(0x1p-14)]; tensor var_296_cast_fp16 = add(x = var_294_cast_fp16, y = var_295_to_fp16)[name = string("op_296_cast_fp16")]; tensor std_y_17_cast_fp16 = sqrt(x = var_296_cast_fp16)[name = string("std_y_17_cast_fp16")]; tensor sep_module_3_tcn_6_norm_gamma_to_fp16 = const()[name = string("sep_module_3_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(287936)))]; tensor var_299_cast_fp16 = mul(x = sep_module_3_tcn_6_norm_gamma_to_fp16, y = var_291_cast_fp16)[name = string("op_299_cast_fp16")]; tensor var_300_cast_fp16 = real_div(x = var_299_cast_fp16, y = std_y_17_cast_fp16)[name = string("op_300_cast_fp16")]; tensor sep_module_3_tcn_6_norm_beta_to_fp16 = const()[name = string("sep_module_3_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(288256)))]; tensor y_8_cast_fp16 = add(x = var_300_cast_fp16, y = sep_module_3_tcn_6_norm_beta_to_fp16)[name = string("y_8_cast_fp16")]; tensor input_43_cast_fp16 = add(x = input_33_cast_fp16, y = y_8_cast_fp16)[name = string("input_43_cast_fp16")]; tensor var_311 = const()[name = string("op_311"), val = tensor([1])]; tensor var_313 = const()[name = string("op_313"), val = tensor([1])]; string input_45_pad_type_0 = const()[name = string("input_45_pad_type_0"), val = string("custom")]; tensor input_45_pad_0 = const()[name = string("input_45_pad_0"), val = tensor([0, 0])]; tensor sep_module_4_tcn_0_weight_to_fp16 = const()[name = string("sep_module_4_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(288576)))]; tensor input_45_cast_fp16 = conv(dilations = var_313, groups = var_56, pad = input_45_pad_0, pad_type = input_45_pad_type_0, strides = var_311, weight = sep_module_4_tcn_0_weight_to_fp16, x = input_43_cast_fp16)[name = string("input_45_cast_fp16")]; fp32 var_317_alpha_1 = const()[name = string("op_317_alpha_1"), val = fp32(0x1.07309cp-1)]; tensor var_317_cast_fp16 = leaky_relu(alpha = fp16(0x1.074p-1), x = input_45_cast_fp16); tensor var_321 = const()[name = string("op_321"), val = tensor([1])]; tensor mean_y_19_cast_fp16 = reduce_mean(axes = var_321, keep_dims = var_61, x = var_317_cast_fp16)[name = string("mean_y_19_cast_fp16")]; tensor var_323_cast_fp16 = sub(x = var_317_cast_fp16, y = mean_y_19_cast_fp16)[name = string("op_323_cast_fp16")]; tensor var_324_cast_fp16 = square(x = var_323_cast_fp16); tensor var_325 = const()[name = string("op_325"), val = tensor([1])]; tensor var_326_cast_fp16 = reduce_mean(axes = var_325, keep_dims = var_61, x = var_324_cast_fp16)[name = string("op_326_cast_fp16")]; fp16 var_327_to_fp16 = const()[name = string("op_327_to_fp16"), val = fp16(0x1p-14)]; tensor var_328_cast_fp16 = add(x = var_326_cast_fp16, y = var_327_to_fp16)[name = string("op_328_cast_fp16")]; tensor std_y_19_cast_fp16 = sqrt(x = var_328_cast_fp16)[name = string("std_y_19_cast_fp16")]; tensor sep_module_4_tcn_2_norm_gamma_to_fp16 = const()[name = string("sep_module_4_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(321408)))]; tensor var_331_cast_fp16 = mul(x = sep_module_4_tcn_2_norm_gamma_to_fp16, y = var_323_cast_fp16)[name = string("op_331_cast_fp16")]; tensor var_332_cast_fp16 = real_div(x = var_331_cast_fp16, y = std_y_19_cast_fp16)[name = string("op_332_cast_fp16")]; tensor sep_module_4_tcn_2_norm_beta_to_fp16 = const()[name = string("sep_module_4_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(321728)))]; tensor input_47_cast_fp16 = add(x = var_332_cast_fp16, y = sep_module_4_tcn_2_norm_beta_to_fp16)[name = string("input_47_cast_fp16")]; tensor input_49_pad_0 = const()[name = string("input_49_pad_0"), val = tensor([0, 0, 0, 0, 32, 0])]; string input_49_mode_0 = const()[name = string("input_49_mode_0"), val = string("constant")]; fp16 const_4_to_fp16 = const()[name = string("const_4_to_fp16"), val = fp16(0x0p+0)]; tensor input_47_cast_fp16_state_input = read_state(input = input_47_cast_fp16_state); tensor input_49_cast_fp16 = slice_update(begin = tensor([0, 0, 32]), end = tensor([1, 128, 36]), end_mask = tensor([false, false, false]), update = input_47_cast_fp16, x = input_47_cast_fp16_state_input); write_state(data = input_49_cast_fp16, input = input_47_cast_fp16_state); tensor var_337 = const()[name = string("op_337"), val = tensor([1])]; tensor var_339 = const()[name = string("op_339"), val = tensor([16])]; string input_51_pad_type_0 = const()[name = string("input_51_pad_type_0"), val = string("custom")]; tensor input_51_pad_0 = const()[name = string("input_51_pad_0"), val = tensor([0, 0])]; tensor sep_module_4_tcn_4_weight_to_fp16 = const()[name = string("sep_module_4_tcn_4_weight_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(322048)))]; tensor input_51_cast_fp16 = conv(dilations = var_339, groups = var_57, pad = input_51_pad_0, pad_type = input_51_pad_type_0, strides = var_337, weight = sep_module_4_tcn_4_weight_to_fp16, x = input_49_cast_fp16)[name = string("input_51_cast_fp16")]; fp32 var_343_alpha_1 = const()[name = string("op_343_alpha_1"), val = fp32(-0x1.4a9904p-6)]; tensor var_343_cast_fp16 = leaky_relu(alpha = fp16(-0x1.4a8p-6), x = input_51_cast_fp16); tensor var_347 = const()[name = string("op_347"), val = tensor([1])]; tensor mean_y_21_cast_fp16 = reduce_mean(axes = var_347, keep_dims = var_61, x = var_343_cast_fp16)[name = string("mean_y_21_cast_fp16")]; tensor var_349_cast_fp16 = sub(x = var_343_cast_fp16, y = mean_y_21_cast_fp16)[name = string("op_349_cast_fp16")]; tensor var_350_cast_fp16 = square(x = var_349_cast_fp16); tensor var_351 = const()[name = string("op_351"), val = tensor([1])]; tensor var_352_cast_fp16 = reduce_mean(axes = var_351, keep_dims = var_61, x = var_350_cast_fp16)[name = string("op_352_cast_fp16")]; fp16 var_353_to_fp16 = const()[name = string("op_353_to_fp16"), val = fp16(0x1p-14)]; tensor var_354_cast_fp16 = add(x = var_352_cast_fp16, y = var_353_to_fp16)[name = string("op_354_cast_fp16")]; tensor std_y_21_cast_fp16 = sqrt(x = var_354_cast_fp16)[name = string("std_y_21_cast_fp16")]; tensor sep_module_4_tcn_6_norm_gamma_to_fp16 = const()[name = string("sep_module_4_tcn_6_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(322880)))]; tensor var_357_cast_fp16 = mul(x = sep_module_4_tcn_6_norm_gamma_to_fp16, y = var_349_cast_fp16)[name = string("op_357_cast_fp16")]; tensor var_358_cast_fp16 = real_div(x = var_357_cast_fp16, y = std_y_21_cast_fp16)[name = string("op_358_cast_fp16")]; tensor sep_module_4_tcn_6_norm_beta_to_fp16 = const()[name = string("sep_module_4_tcn_6_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(323200)))]; tensor y_10_cast_fp16 = add(x = var_358_cast_fp16, y = sep_module_4_tcn_6_norm_beta_to_fp16)[name = string("y_10_cast_fp16")]; tensor input_53_cast_fp16 = add(x = input_43_cast_fp16, y = y_10_cast_fp16)[name = string("input_53_cast_fp16")]; tensor var_369 = const()[name = string("op_369"), val = tensor([1])]; tensor var_371 = const()[name = string("op_371"), val = tensor([1])]; string input_2_pad_type_0 = const()[name = string("input_2_pad_type_0"), val = string("custom")]; tensor input_2_pad_0 = const()[name = string("input_2_pad_0"), val = tensor([0, 0])]; tensor sep_module_5_tcn_0_weight_to_fp16 = const()[name = string("sep_module_5_tcn_0_weight_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(323520)))]; tensor input_2_cast_fp16 = conv(dilations = var_371, groups = var_56, pad = input_2_pad_0, pad_type = input_2_pad_type_0, strides = var_369, weight = sep_module_5_tcn_0_weight_to_fp16, x = input_53_cast_fp16)[name = string("input_2_cast_fp16")]; fp32 var_375_alpha_1 = const()[name = string("op_375_alpha_1"), val = fp32(0x1.19fad6p-1)]; tensor var_375_cast_fp16 = leaky_relu(alpha = fp16(0x1.1ap-1), x = input_2_cast_fp16); tensor var_379 = const()[name = string("op_379"), val = tensor([1])]; tensor mean_y_2_cast_fp16 = reduce_mean(axes = var_379, keep_dims = var_61, x = var_375_cast_fp16)[name = string("mean_y_2_cast_fp16")]; tensor var_381_cast_fp16 = sub(x = var_375_cast_fp16, y = mean_y_2_cast_fp16)[name = string("op_381_cast_fp16")]; tensor var_382_cast_fp16 = square(x = var_381_cast_fp16); tensor var_383 = const()[name = string("op_383"), val = tensor([1])]; tensor var_384_cast_fp16 = reduce_mean(axes = var_383, keep_dims = var_61, x = var_382_cast_fp16)[name = string("op_384_cast_fp16")]; fp16 var_385_to_fp16 = const()[name = string("op_385_to_fp16"), val = fp16(0x1p-14)]; tensor var_386_cast_fp16 = add(x = var_384_cast_fp16, y = var_385_to_fp16)[name = string("op_386_cast_fp16")]; tensor std_y_2_cast_fp16 = sqrt(x = var_386_cast_fp16)[name = string("std_y_2_cast_fp16")]; tensor sep_module_5_tcn_2_norm_gamma_to_fp16 = const()[name = string("sep_module_5_tcn_2_norm_gamma_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(356352)))]; tensor var_389_cast_fp16 = mul(x = sep_module_5_tcn_2_norm_gamma_to_fp16, y = var_381_cast_fp16)[name = string("op_389_cast_fp16")]; tensor var_390_cast_fp16 = real_div(x = var_389_cast_fp16, y = std_y_2_cast_fp16)[name = string("op_390_cast_fp16")]; tensor sep_module_5_tcn_2_norm_beta_to_fp16 = const()[name = string("sep_module_5_tcn_2_norm_beta_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/sc-vad-nnet.weight.bin"), offset = uint64(356672)))]; tensor input_4_cast_fp16 = add(x = var_390_cast_fp16, y = sep_module_5_tcn_2_norm_beta_to_fp16)[name = string("input_4_cast_fp16")]; tensor input_6_pad_0 = const()[name = string("input_6_pad_0"), val = tensor([0, 0, 0, 0, 64, 0])]; string input_6_mode_0 = const()[name = string("input_6_mode_0"), val = string("constant")]; fp16 const_5_to_fp16 = const()[name = string("const_5_to_fp16"), val = fp16(0x0p+0)]; tensor input_4_cast_fp16_state_input = read_state(input = input_4_cast_fp16_state); tensor input_6_cast_fp16 = slice_update(begin = tensor([0, 0, 64]), end = tensor([1, 128, 68]), end_mask = tensor([false, false, false]), update = input_4_cast_fp16, x = input_4_cast_fp16_state_input); write_state(data = input_6_cast_fp16, input = input_4_cast_fp16_state); tensor var_395 = const()[name = string("op_395"), val = tensor