program(1.0)
[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3520.4.1"}, {"coremlc-version", "3520.5.1"}, {"coremltools-component-torch", "2.7.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "9.0b1"}})]
{
    func main<ios17>(tensor<fp32, [1, 512, 188]> encoder_output) {
            tensor<int32, []> var_4 = const()[name = tensor<string, []>("op_4"), val = tensor<int32, []>(-1)];
            tensor<string, []> var_18_pad_type_0 = const()[name = tensor<string, []>("op_18_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> var_18_strides_0 = const()[name = tensor<string, []>("op_18_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> var_18_pad_0 = const()[name = tensor<string, []>("op_18_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> var_18_dilations_0 = const()[name = tensor<string, []>("op_18_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> var_18_groups_0 = const()[name = tensor<string, []>("op_18_groups_0"), val = tensor<int32, []>(1)];
            tensor<string, []> encoder_output_to_fp16_dtype_0 = const()[name = tensor<string, []>("encoder_output_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
            tensor<fp16, [1025, 512, 1]> module_decoder_layers_0_weight_to_fp16 = const()[name = tensor<string, []>("module_decoder_layers_0_weight_to_fp16"), val = tensor<fp16, [1025, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
            tensor<fp16, [1025]> module_decoder_layers_0_bias_to_fp16 = const()[name = tensor<string, []>("module_decoder_layers_0_bias_to_fp16"), val = tensor<fp16, [1025]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1049728)))];
            tensor<fp16, [1, 512, 188]> encoder_output_to_fp16 = cast(dtype = encoder_output_to_fp16_dtype_0, x = encoder_output)[name = tensor<string, []>("cast_1")];
            tensor<fp16, [1, 1025, 188]> var_18_cast_fp16 = conv(bias = module_decoder_layers_0_bias_to_fp16, dilations = var_18_dilations_0, groups = var_18_groups_0, pad = var_18_pad_0, pad_type = var_18_pad_type_0, strides = var_18_strides_0, weight = module_decoder_layers_0_weight_to_fp16, x = encoder_output_to_fp16)[name = tensor<string, []>("op_18_cast_fp16")];
            tensor<int32, [3]> input_perm_0 = const()[name = tensor<string, []>("input_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1025]> input_cast_fp16 = transpose(perm = input_perm_0, x = var_18_cast_fp16)[name = tensor<string, []>("transpose_0")];
            tensor<fp16, [1, 188, 1025]> out_objects_softmax_cast_fp16 = softmax(axis = var_4, x = input_cast_fp16)[name = tensor<string, []>("out_objects_softmax_cast_fp16")];
            tensor<fp32, []> out_objects_epsilon_0 = const()[name = tensor<string, []>("out_objects_epsilon_0"), val = tensor<fp32, []>(0x1p-149)];
            tensor<fp16, [1, 188, 1025]> out_objects_cast_fp16 = log(epsilon = out_objects_epsilon_0, x = out_objects_softmax_cast_fp16)[name = tensor<string, []>("out_objects_cast_fp16")];
            tensor<string, []> out_objects_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("out_objects_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<fp32, [1, 188, 1025]> ctc_logits = cast(dtype = out_objects_cast_fp16_to_fp32_dtype_0, x = out_objects_cast_fp16)[name = tensor<string, []>("cast_0")];
        } -> (ctc_logits);
}