Keras DropBlock

Implementation of DropBlock

Install

bash pip install keras-drop-block

Usage

See fashion mnist demo.

Issues

module 'keras' has no attribute 'applications'

opened on 2021-06-20 10:03:30 by SOUMEE2000

18 utils = keras.utils 19 activations = keras.activations ---> 20 applications = keras.applications 21 backend = keras.backend 22 datasets = keras.datasets

AttributeError: module 'keras' has no attribute 'applications'

Could anyone please help out a bit?

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

opened on 2020-03-03 11:23:14 by 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 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 "", line 3, in raise_from TypeError: Dimension value must be integer or None or have an index method, got

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 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 ```