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April 24, 2017 18:46
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This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters. Learn more about bidirectional Unicode charactersOriginal file line number Diff line number Diff line change @@ -0,0 +1,141 @@ In [9]: model.predict(np.random.random((10, 3, 2))) W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations. --------------------------------------------------------------------------- InvalidArgumentError Traceback (most recent call last) /home/pedro/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args) 1021 try: -> 1022 return fn(*args) 1023 except errors.OpError as e: /home/pedro/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata) 1003 feed_dict, fetch_list, target_list, -> 1004 status, run_metadata) 1005 /home/pedro/anaconda3/lib/python3.6/contextlib.py in __exit__(self, type, value, traceback) 88 try: ---> 89 next(self.gen) 90 except StopIteration: /home/pedro/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py in raise_exception_on_not_ok_status() 468 compat.as_text(pywrap_tensorflow.TF_Message(status)), --> 469 pywrap_tensorflow.TF_GetCode(status)) 470 finally: InvalidArgumentError: You must feed a value for placeholder tensor 'time_distributed_1/keras_learning_phase' with dtype bool [[Node: time_distributed_1/keras_learning_phase = Placeholder[dtype=DT_BOOL, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]] During handling of the above exception, another exception occurred: InvalidArgumentError Traceback (most recent call last) <ipython-input-9-4104792c4c07> in <module>() ----> 1 model.predict(np.random.random((10, 3, 2))) /home/pedro/software/keras/keras/models.py in predict(self, x, batch_size, verbose) 897 if self.model is None: 898 self.build() --> 899 return self.model.predict(x, batch_size=batch_size, verbose=verbose) 900 901 def predict_on_batch(self, x): /home/pedro/software/keras/keras/engine/training.py in predict(self, x, batch_size, verbose) 1578 f = self.predict_function 1579 return self._predict_loop(f, ins, -> 1580 batch_size=batch_size, verbose=verbose) 1581 1582 def train_on_batch(self, x, y, /home/pedro/software/keras/keras/engine/training.py in _predict_loop(self, f, ins, batch_size, verbose) 1205 ins_batch = _slice_arrays(ins, batch_ids) 1206 -> 1207 batch_outs = f(ins_batch) 1208 if not isinstance(batch_outs, list): 1209 batch_outs = [batch_outs] /home/pedro/software/keras/keras/backend/tensorflow_backend.py in __call__(self, inputs) 2151 session = get_session() 2152 updated = session.run(self.outputs + [self.updates_op], -> 2153 feed_dict=feed_dict) 2154 return updated[:len(self.outputs)] 2155 /home/pedro/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata) 765 try: 766 result = self._run(None, fetches, feed_dict, options_ptr, --> 767 run_metadata_ptr) 768 if run_metadata: 769 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr) /home/pedro/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata) 963 if final_fetches or final_targets: 964 results = self._do_run(handle, final_targets, final_fetches, --> 965 feed_dict_string, options, run_metadata) 966 else: 967 results = [] /home/pedro/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata) 1013 if handle is None: 1014 return self._do_call(_run_fn, self._session, feed_dict, fetch_list, -> 1015 target_list, options, run_metadata) 1016 else: 1017 return self._do_call(_prun_fn, self._session, handle, feed_dict, /home/pedro/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args) 1033 except KeyError: 1034 pass -> 1035 raise type(e)(node_def, op, message) 1036 1037 def _extend_graph(self): InvalidArgumentError: You must feed a value for placeholder tensor 'time_distributed_1/keras_learning_phase' with dtype bool [[Node: time_distributed_1/keras_learning_phase = Placeholder[dtype=DT_BOOL, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]] Caused by op 'time_distributed_1/keras_learning_phase', defined at: File "/home/pedro/anaconda3/bin/ipython", line 6, in <module> sys.exit(IPython.start_ipython()) File "/home/pedro/anaconda3/lib/python3.6/site-packages/IPython/__init__.py", line 119, in start_ipython return launch_new_instance(argv=argv, **kwargs) File "/home/pedro/anaconda3/lib/python3.6/site-packages/traitlets/config/application.py", line 658, in launch_instance app.start() File "/home/pedro/anaconda3/lib/python3.6/site-packages/IPython/terminal/ipapp.py", line 348, in start self.shell.mainloop() File "/home/pedro/anaconda3/lib/python3.6/site-packages/IPython/terminal/interactiveshell.py", line 440, in mainloop self.interact() File "/home/pedro/anaconda3/lib/python3.6/site-packages/IPython/terminal/interactiveshell.py", line 431, in interact self.run_cell(code, store_history=True) File "/home/pedro/anaconda3/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2717, in run_cell interactivity=interactivity, compiler=compiler, result=result) File "/home/pedro/anaconda3/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2827, in run_ast_nodes if self.run_code(code, result): File "/home/pedro/anaconda3/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2881, in run_code exec(code_obj, self.user_global_ns, self.user_ns) File "<ipython-input-7-7feb8d6104c1>", line 1, in <module> model.add(wrappers.TimeDistributed(core.Dropout(.5), input_shape=(3, 2))) File "/home/pedro/software/keras/keras/models.py", line 430, in add layer(x) File "/home/pedro/software/keras/keras/engine/topology.py", line 585, in __call__ output = self.call(inputs, **kwargs) File "/home/pedro/software/keras/keras/layers/wrappers.py", line 177, in call y = self.layer.call(inputs) # (num_samples * timesteps, ...) File "/home/pedro/software/keras/keras/layers/core.py", line 111, in call training=training) File "/home/pedro/software/keras/keras/backend/tensorflow_backend.py", line 2483, in in_train_phase training = learning_phase() File "/home/pedro/software/keras/keras/backend/tensorflow_backend.py", line 103, in learning_phase name='keras_learning_phase') File "/home/pedro/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 1520, in placeholder name=name) File "/home/pedro/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/gen_array_ops.py", line 2149, in _placeholder name=name) File "/home/pedro/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 763, in apply_op op_def=op_def) File "/home/pedro/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 2395, in create_op original_op=self._default_original_op, op_def=op_def) File "/home/pedro/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1264, in __init__ self._traceback = _extract_stack() InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'time_distributed_1/keras_learning_phase' with dtype bool [[Node: time_distributed_1/keras_learning_phase = Placeholder[dtype=DT_BOOL, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]