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dmlc / keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on MXNet, Theano or TensorFlow.
http://keras.io/
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errors while call the keras.applications.inception_v3 #87

Open heroxrq opened 6 years ago

heroxrq commented 6 years ago

I turn my keras backend from tensorflow to mxnet to use mxnet's multi gpu training. However the code I run successfully in keras tensorflow backend seems not compatible with keras mxnet backend. It prints the following:

Using MXNet backend. train and valid generator is ok steps_per_epoch: 55673 validation_steps: 1236 Traceback (most recent call last): File "train_inception_v3_transfer_learning.py", line 64, in base_model = InceptionV3(include_top=False, weights=None, input_shape=(3, INPUT_HEIGHT, INPUT_WIDTH)) File "/home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/keras/applications/inception_v3.py", line 151, in InceptionV3 (3, 3), strides=(1, 1), border_mode='same')(x) File "/home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/keras/engine/topology.py", line 572, in call self.add_inbound_node(inbound_layers, node_indices, tensor_indices) File "/home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/keras/engine/topology.py", line 635, in add_inbound_node Node.create_node(self, inbound_layers, node_indices, tensor_indices) File "/home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/keras/engine/topology.py", line 166, in create_node output_tensors = to_list(outbound_layer.call(input_tensors[0], mask=input_masks[0])) File "/home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/keras/layers/pooling.py", line 160, in call dim_ordering=self.dim_ordering) File "/home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/keras/layers/pooling.py", line 251, in _pooling_function border_mode, dim_ordering, pool_mode='avg') File "/home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/keras/backend/mxnet_backend.py", line 33, in func_wrapper train_ret = func(*args, **kwargs) File "/home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/keras/backend/mxnet_backend.py", line 2912, in pool2d stride=strides) File "", line 39, in Pooling File "/home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/mxnet/_ctypes/symbol.py", line 127, in _symbol_creator ctypes.byref(sym_handle))) File "/home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/mxnet/base.py", line 129, in check_call raise MXNetError(py_str(_LIB.MXGetLastError())) mxnet.base.MXNetError: Invalid Input: 'same', valid values are: {'full', 'valid'}, in operator Pooling(name="", stride="(1, 1)", pooling_convention="same", pool_type="avg", kernel="(3, 3)")

DSLituiev commented 6 years ago

I am getting an error even without specifying input shape with this two simple lines:

from keras.applications.inception_v3 import InceptionV3
#Using MXNet backend.
base_model = InceptionV3(weights='imagenet',
                               include_top=False,
                                #pooling=None,
                               )

error:

[21:10:59] /home/travis/build/dmlc/mxnet-distro/mxnet-build/dmlc-core/include/dmlc/logging.h:308: [21:10:59] src/operator/./pooling-inl.h:214: Check failed: param_.kernel[0] <= dshape[2] + 2 * param_.pad[0] kernel size (3) exceeds input (0 padded to 0) Stack trace returned 10 entries: [bt] (0) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(+0xec23c) [0x7fec5a44123c] [bt] (1) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x1170ca2) [0x7fec5b4c5ca2] [bt] (2) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(+0xf90817) [0x7fec5b2e5817] [bt] (3) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x16e9531) [0x7fec5ba3e531] [bt] (4) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x16ead42) [0x7fec5ba3fd42] [bt] (5) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x16eb686) [0x7fec5ba40686] [bt] (6) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x16d4e88) [0x7fec5ba29e88] [bt] (7) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(+0xe049fe) [0x7fec5b1599fe] [bt] (8) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(+0xe0732e) [0x7fec5b15c32e] [bt] (9) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(MXSymbolInferShape+0x156f) [0x7fec5b154d2f] ------------------------------------------------------------------------ MXNetError Traceback (most recent call last) in () 1 base_model = InceptionV3(weights='imagenet', ----> 2 include_top=False, 3 #pooling=None, 4 ) 5 ~/anaconda3/envs/mxnet/lib/python3.5/site-packages/keras/applications/inception_v3.py in InceptionV3(include_top, weights, input_tensor, input_shape, classes) 133 x = MaxPooling2D((3, 3), strides=(2, 2))(x) 134 --> 135 x = conv2d_bn(x, 80, 1, 1, border_mode='valid') 136 x = conv2d_bn(x, 192, 3, 3, border_mode='valid') 137 x = MaxPooling2D((3, 3), strides=(2, 2))(x) ~/anaconda3/envs/mxnet/lib/python3.5/site-packages/keras/applications/inception_v3.py in conv2d_bn(x, nb_filter, nb_row, nb_col, border_mode, subsample, name) 56 activation='relu', 57 border_mode=border_mode, ---> 58 name=conv_name)(x) 59 x = BatchNormalization(axis=bn_axis, name=bn_name)(x) 60 return x ~/anaconda3/envs/mxnet/lib/python3.5/site-packages/keras/engine/topology.py in __call__(self, x, mask) 527 # Raise exceptions in case the input is not compatible 528 # with the input_spec specified in the layer constructor. --> 529 self.assert_input_compatibility(x) 530 531 # Collect input shapes to build layer. ~/anaconda3/envs/mxnet/lib/python3.5/site-packages/keras/engine/topology.py in assert_input_compatibility(self, input) 462 str(K.ndim(x))) 463 else: --> 464 if K.ndim(x) != spec.ndim: 465 raise ValueError('Input ' + str(input_index) + 466 ' is incompatible with layer ' + ~/anaconda3/envs/mxnet/lib/python3.5/site-packages/keras/backend/mxnet_backend.py in ndim(x) 632 ``` 633 """ --> 634 s = shape(x) 635 if s is None: 636 return 0 ~/anaconda3/envs/mxnet/lib/python3.5/site-packages/keras/backend/mxnet_backend.py in shape(x) 577 # return tuple([0 if x is None else x for x in x._keras_shape]) 578 if isinstance(x, KerasSymbol): --> 579 return x.get_shape() 580 else: 581 return None ~/anaconda3/envs/mxnet/lib/python3.5/site-packages/keras/backend/mxnet_backend.py in get_shape(self) 256 return self.tensor.shape 257 else: --> 258 _, out_shape, _ = self.symbol.infer_shape_partial() 259 return out_shape[0] 260 ~/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/symbol.py in infer_shape_partial(self, *args, **kwargs) 1048 The order is same as the order of list_auxiliary_states(). 1049 """ -> 1050 return self._infer_shape_impl(True, *args, **kwargs) 1051 1052 def _infer_shape_impl(self, partial, *args, **kwargs): ~/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/symbol.py in _infer_shape_impl(self, partial, *args, **kwargs) 1105 ctypes.byref(aux_shape_ndim), 1106 ctypes.byref(aux_shape_data), -> 1107 ctypes.byref(complete))) 1108 if complete.value != 0: 1109 arg_shapes = [ ~/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/base.py in check_call(ret) 127 """ 128 if ret != 0: --> 129 raise MXNetError(py_str(_LIB.MXGetLastError())) 130 131 if sys.version_info[0] < 3: MXNetError: Error in operator pooling0: [21:10:59] src/operator/./pooling-inl.h:214: Check failed: param_.kernel[0] <= dshape[2] + 2 * param_.pad[0] kernel size (3) exceeds input (0 padded to 0) Stack trace returned 10 entries: [bt] (0) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(+0xec23c) [0x7fec5a44123c] [bt] (1) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x1170ca2) [0x7fec5b4c5ca2] [bt] (2) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(+0xf90817) [0x7fec5b2e5817] [bt] (3) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x16e9531) [0x7fec5ba3e531] [bt] (4) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x16ead42) [0x7fec5ba3fd42] [bt] (5) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x16eb686) [0x7fec5ba40686] [bt] (6) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x16d4e88) [0x7fec5ba29e88] [bt] (7) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(+0xe049fe) [0x7fec5b1599fe] [bt] (8) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(+0xe0732e) [0x7fec5b15c32e] [bt] (9) /home/ubuntu/anaconda3/envs/mxnet/lib/python3.5/site-packages/mxnet/libmxnet.so(MXSymbolInferShape+0x156f) [0x7fec5b154d2f]
sandeep-krishnamurthy commented 6 years ago

Will look in to this.