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I tried implementing your fixes @tackoo for my data of 1600 rows 103 columns. I've tried training the data earlier with Conv1D in a sequential model with input (103,1) but when I try to use this inpus shape for this ResNet model I get this error: ValueError: Input 0 of layer conv1 is incompatible with the layer: : expected min_ndim=4, found ndim=3. Full shape received: (None, 103, 1)
When load a model
`
# save model
model_json = model.to_json()
with open("model.json", "w") as json_file:
json_file.write(model_json)
`
I get this error:
Shape must be rank 3 but is rank 4 for 'padding_conv1_2/Pad'
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