Error while converting pytorch model to core-ml
C = torch.cat((A,B),1)


shape of tensors: 

A is (1, 128, 128, 256)
B is (1, 1, 128, 256)


Expected C value is (1, 129, 128, 256)

This code is working on pytorch, but while converting to core-ml it gives me below error:

"Error while converting op of type: {}. Error message: {}\n".format(node.op_type, err_message, )
TypeError: Error while converting op of type: Concat. Error message: unable to translate constant array shape to CoreML shape"


It was coremltools version related issue. Tried with latest beta coremltools 3.0b2.

Following works without any error with latest beta.

import torch

class cat_model(torch.nn.Module):
    def __init__(self):
        super(cat_model, self).__init__()

    def forward(self, a, b):
        c = torch.cat((a, b), 1)
        # print(c.shape)
        return c

a = torch.randn((1, 128, 128, 256))
b = torch.randn((1, 1, 128, 256))

model = cat_model()
torch.onnx.export(model, (a, b), 'cat_model.onnx')

import onnx
model = onnx.load('cat_model.onnx')
onnx.checker.check_model(model)
print(onnx.helper.printable_graph(model.graph))

from onnx_coreml import convert
mlmodel = convert(model)

