Open linetor opened 7 years ago
MaJieCornell
commented
7 years ago I also encounter this issue when trying to use Inception_v3 in Keras. I think there is an issue in python2.7/site-packages/keras/backend/mxnet_backend.py when convert the argument from Keras to MXnet. They are not compatible.
Is there anyone look into this issue?
Thanks
heroxrq
commented
7 years ago @mli @pluskid @superbobry @MaJieCornell I meet the problem too (see #87 ). However, after I add the following 2 lines in mxnet_backend.py pool2d() to convert keras 'same' to mxnet 'full':
if border_mode == 'same':
border_mode = 'full'
Using MXNet backend. train and valid generator is ok steps_per_epoch: 55673 validation_steps: 1236 [10:19:53] /home/travis/build/dmlc/mxnet-distro/mxnet-build/dmlc-core/include/dmlc/logging.h:308: [10:19:53] src/operator/./concat-inl.h:184: Check failed: shape_assign(&(*in_shape)[i], dshape) Incompatible input shape: expected (0,0,20,20), got (0,32,18,18)
Stack trace returned 10 entries: [bt] (0) /home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x1d57cc) [0x2b02257607cc] [bt] (1) /home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x1005a79) [0x2b0226590a79] [bt] (2) /home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/mxnet/libmxnet.so(+0xf9d2d7) [0x2b02265282d7] [bt] (3) /home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x2d6d621) [0x2b02282f8621] [bt] (4) /home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x2d6ee32) [0x2b02282f9e32] [bt] (5) /home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x2d6f776) [0x2b02282fa776] [bt] (6) /home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x2d58f78) [0x2b02282e3f78] [bt] (7) /home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/mxnet/libmxnet.so(+0xe0fcae) [0x2b022639acae] [bt] (8) /home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/mxnet/libmxnet.so(+0xe125de) [0x2b022639d5de] [bt] (9) /home/xierenqiang/install/anaconda3/lib/python3.6/site-packages/mxnet/libmxnet.so(MXSymbolInferShape+0x156f) [0x2b0226395fdf]
Traceback (most recent call last):
File "train_inception_v3_transfer_learning.py", line 64, in
I want to use keras.applications.inception_v3 model. After I load that model it, there is an error about pooling layer.
Error Message :----> 1 InceptionV3(include_top=True,input_tensor=None, input_shape=None,weights=None)
/pang/linetor/miniconda2/envs/py27/lib/python2.7/site-packages/keras/applications/inception_v3.pyc in InceptionV3(include_top, weights, input_tensor, input_shape, classes) 149 150 branch_pool = AveragePooling2D( --> 151 (3, 3), strides=(1, 1), border_mode='same')(x) 152 branch_pool = conv2d_bn(branch_pool, 32, 1, 1) 153 x = merge([branch1x1, branch5x5, branch3x3dbl, branch_pool],
/pang/linetor/miniconda2/envs/py27/lib/python2.7/site-packages/keras/engine/topology.pyc in call(self, x, mask) 570 if inbound_layers: 571 # This will call layer.build() if necessary. --> 572 self.add_inbound_node(inbound_layers, node_indices, tensor_indices) 573 # Outputs were already computed when calling self.add_inbound_node. 574 outputs = self.inbound_nodes[-1].output_tensors
/pang/linetor/miniconda2/envs/py27/lib/python2.7/site-packages/keras/engine/topology.pyc in add_inbound_node(self, inbound_layers, node_indices, tensor_indices) 633 # creating the node automatically updates self.inbound_nodes 634 # as well as outbound_nodes on inbound layers. --> 635 Node.create_node(self, inbound_layers, node_indices, tensor_indices) 636 637 def get_output_shape_for(self, input_shape):
/pang/linetor/miniconda2/envs/py27/lib/python2.7/site-packages/keras/engine/topology.pyc in create_node(cls, outbound_layer, inbound_layers, node_indices, tensor_indices) 164 165 if len(input_tensors) == 1: --> 166 output_tensors = to_list(outbound_layer.call(input_tensors[0], mask=input_masks[0])) 167 output_masks = to_list(outbound_layer.compute_mask(input_tensors[0], input_masks[0])) 168 # TODO: try to auto-infer shape
/pang/linetor/miniconda2/envs/py27/lib/python2.7/site-packages/keras/layers/pooling.pyc in call(self, x, mask) 158 strides=self.strides, 159 border_mode=self.border_mode, --> 160 dim_ordering=self.dim_ordering) 161 return output 162
/pang/linetor/miniconda2/envs/py27/lib/python2.7/site-packages/keras/layers/pooling.pyc in _pooling_function(self, inputs, pool_size, strides, border_mode, dim_ordering) 249 border_mode, dim_ordering): 250 output = K.pool2d(inputs, pool_size, strides, --> 251 border_mode, dim_ordering, pool_mode='avg') 252 return output 253
/pang/linetor/miniconda2/envs/py27/lib/python2.7/site-packages/keras/backend/mxnet_backend.pyc in func_wrapper(*args, kwargs) 31 old = learning_phase() 32 set_learning_phase(1) ---> 33 train_ret = func(*args, *kwargs) 34 set_learning_phase(0) 35 test_ret = func(args, kwargs)
/pang/linetor/miniconda2/envs/py27/lib/python2.7/site-packages/keras/backend/mxnet_backend.pyc in pool2d(x, pool_size, strides, border_mode, dim_ordering, pool_mode) 2910 x = _preprocess_convnd_input(x, dim_ordering) 2911 s = mx.sym.Pooling(data=x.symbol, kernel=pool_size, pool_type=pool_mode, pooling_convention=border_mode, -> 2912 stride=strides) 2913 out = _postprocess_convnd_output(KerasSymbol(s), dim_ordering) 2914 return out
/pang/linetor/.local/lib/python2.7/site-packages/mxnet/symbol.pyc in Pooling(data, global_pool, cudnn_off, kernel, pool_type, pooling_convention, stride, pad, name, attr, out, **kwargs)
/pang/linetor/.local/lib/python2.7/site-packages/mxnet/_ctypes/symbol.pyc in _symbol_creator(handle, args, kwargs, keys, vals, name) 125 c_array(ctypes.c_char_p, [c_str(i) for i in keys]), 126 c_array(ctypes.c_char_p, [c_str(str(i)) for i in vals]), --> 127 ctypes.byref(sym_handle))) 128 129 if args and kwargs:
/pang/linetor/.local/lib/python2.7/site-packages/mxnet/base.pyc 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: Invalid Input: 'same', valid values are: {'full', 'valid'}, in operator Pooling(name="", stride="(1, 1)", pooling_convention="same", pool_type="avg", kernel="(3, 3)")
If I read error message, I think argument about border _mode. In keras 1.2.2, Pooling layer 's argument : border_mode need to be in ('valid' or 'same'). But by using mxnet, back-end it says {'full', 'valid'}. If I use "same', mxnet makes a issue. If I use 'full', keras makes issue. So I can't implement InceptionResNetV2.
Is there any comment about this?
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