ypeError: An op outside of the function building code is being passed a "Graph" tensor

[ma7555]

Running the mnist.py demo, receive the following error

Traceback (most recent call last):
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\tensorflow\python\ops\array_ops.py", line 2953, in ones
    tensor_shape.TensorShape(shape))
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\tensorflow\python\framework\tensor_shape.py", line 771, in __init__
    self._dims = [as_dimension(d) for d in dims_iter]
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\tensorflow\python\framework\tensor_shape.py", line 771, in <listcomp>
    self._dims = [as_dimension(d) for d in dims_iter]
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\tensorflow\python\framework\tensor_shape.py", line 716, in as_dimension
    return Dimension(value)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\tensorflow\python\framework\tensor_shape.py", line 200, in __init__
    None)
  File "<string>", line 3, in raise_from
TypeError: Dimension value must be integer or None or have an __index__ method, got <tf.Tensor 'strided_slice:0' shape=() dtype=int32>

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 6328, in pack
    values, "axis", axis)
tensorflow.python.eager.core._FallbackException: This function does not handle the case of the path where all inputs are not already EagerTensors.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "c:/Users/ma7555/Documents/Kaggle/bengaliai-cv19/mnist.py", line 75, in <module>
    drop_block_model = get_drop_block_model()
  File "c:/Users/ma7555/Documents/Kaggle/bengaliai-cv19/mnist.py", line 56, in get_drop_block_model
    model.add(DropBlock2D(input_shape=(28, 28, 1), block_size=7, keep_prob=0.8, name='Input-Dropout'))
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\keras\engine\sequential.py", line 166, in add
    layer(x)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py", line 75, in symbolic_fn_wrapper
    return func(*args, **kwargs)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\keras\engine\base_layer.py", line 489, in __call__
    output = self.call(inputs, **kwargs)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\keras_drop_block\drop_block.py", line 200, in call
    return K.in_train_phase(dropped_inputs, inputs, training=training)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py", line 75, in symbolic_fn_wrapper
    return func(*args, **kwargs)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py", line 3214, in in_train_phase
    x = switch(training, x, alt)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py", line 75, in symbolic_fn_wrapper
    return func(*args, **kwargs)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py", line 3147, in switch
    else_expression_fn)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\tensorflow\python\ops\control_flow_ops.py", line 1392, in cond_for_tf_v2
    return cond(pred, true_fn=true_fn, false_fn=false_fn, strict=True, name=name)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\tensorflow\python\util\deprecation.py", line 507, in new_func
    return func(*args, **kwargs)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\tensorflow\python\ops\control_flow_ops.py", line 1177, in cond
    return cond_v2.cond_v2(pred, true_fn, false_fn, name)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\tensorflow\python\ops\cond_v2.py", line 83, in cond_v2
    op_return_value=pred)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\tensorflow\python\framework\func_graph.py", line 981, in func_graph_from_py_func
    func_outputs = python_func(*func_args, **func_kwargs)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\keras_drop_block\drop_block.py", line 193, in dropped_inputs
    mask = self._compute_drop_mask(shape)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\keras_drop_block\drop_block.py", line 174, in _compute_drop_mask
    mask *= self._compute_valid_seed_region(height, width)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\keras_drop_block\drop_block.py", line 166, in _compute_valid_seed_region
    K.ones((height, width)),
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py", line 996, in ones
    v = tf.ones(shape=shape, dtype=dtype, name=name)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\tensorflow\python\ops\array_ops.py", line 2956, in ones
    shape = ops.convert_to_tensor(shape, dtype=dtypes.int32)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 1341, in convert_to_tensor
    ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\tensorflow\python\ops\array_ops.py", line 1449, in _autopacking_conversion_function
    return _autopacking_helper(v, dtype, name or "packed")
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\tensorflow\python\ops\array_ops.py", line 1355, in _autopacking_helper
    return gen_array_ops.pack(list_or_tuple, name=name)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 6333, in pack
    values, axis=axis, name=name, ctx=_ctx)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 6375, in pack_eager_fallback
    ctx=ctx, name=name)
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\tensorflow\python\eager\execute.py", line 75, in quick_execute
    raise e
  File "C:\Users\ma7555\Anaconda3\lib\site-packages\tensorflow\python\eager\execute.py", line 60, in quick_execute
    inputs, attrs, num_outputs)
TypeError: An op outside of the function building code is being passed
a "Graph" tensor. It is possible to have Graph tensors
leak out of the function building context by including a
tf.init_scope in your function building code.
For example, the following function will fail:
  @tf.function
  def has_init_scope():
    my_constant = tf.constant(1.)
    with tf.init_scope():
      added = my_constant * 2
The graph tensor has name: strided_slice:0

[greatsharma]

I am also getting this error. @CyberZHG please rectify this.

@ma7555 did you find any other solution compatible with tensorflow and keras. If yes then please share.