Google Colab TensorFlow model.fit() error-CodePudding

Hi Im new to Stack overflow. Im having trouble with my code, I was at model.fit() and when I entered a value at the epochs and ran the code I got an error. Here is the code for the model.fit:

model.fit( train_ds, validation_data = valid_ds, epochs = 10 )

and below here is the error I got:

ValueError Traceback (most recent call last) in () 2 train_ds, 3 validation_data = valid_ds, ----> 4 epochs = 10 5 )

1 frames /usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/func_graph.py in autograph_handler(*args, **kwargs) 1145 except Exception as e: # pylint:disable=broad-except 1146 if hasattr(e, "ag_error_metadata"): -> 1147 raise e.ag_error_metadata.to_exception(e) 1148 else: 1149 raise

ValueError: in user code:

File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1021, in train_function  *
    return step_function(self, iterator)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1010, in step_function  **
    outputs = model.distribute_strategy.run(run_step, args=(data,))
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1000, in run_step  **
    outputs = model.train_step(data)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 859, in train_step
    y_pred = self(x, training=True)
File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 67, in error_handler
    raise e.with_traceback(filtered_tb) from None
File "/usr/local/lib/python3.7/dist-packages/keras/layers/convolutional.py", line 305, in compute_output_shape
    f'One of the dimensions in the output is <= 0 '

ValueError: Exception encountered when calling layer "sequential_3" (type Sequential).

One of the dimensions in the output is <= 0 due to downsampling in conv2d_280. Consider increasing the input size. Received input shape [None, 32, 32, 3] which would produce output shape with a zero or negative value in a dimension.

Call arguments received:
  • inputs=tf.Tensor(shape=(None, 32, 32, 3), dtype=float32)
  • training=True
  • mask=None

Can someone assist me with this? Thanks in advance

CodePudding user response：

Probably you need to upscale the size of your image which you are feeding into the CNN. 360x360x3 is a standard one. Your image size is too small, hence it is not able to build the model fully.

CodePudding user response：

***Probably you need to upscale the size of your image which you are feeding into the CNN. 360x360x3 is a standard one. Your image size is too small, hence it is not able to build the model fully.