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- array([array([65, 3, 96, 94], dtype=int32), array([88], dtype=int32),
- array([113, 52, 106, 57, 3, 86], dtype=int32),
- array([88, 3, 23, 91], dtype=int32), ... ])
- for fold, (train_idx, dev_idx) in enumerate(sss.split(X, y)):
- X_train = X[train_idx]
- y_train = y[train_idx]
- X_dev = X[dev_idx]
- y_dev = y[dev_idx]
- tf.reset_default_graph()
- with tf.Session() as sess:
- features_placeholder = tf.placeholder(tf.int32, [None, None], name='input_x')
- labels_placeholder = tf.placeholder(tf.int32, [None, num_classes], name='input_y')
- dataset = tf.data.Dataset.from_tensor_slices((features_placeholder, labels_placeholder))
- dataset = dataset.shuffle(buffer_size=len(train_idx))
- dataset = dataset.padded_batch(batch_size, padded_shapes=([None], [None]), padding_values=(1, 0))
- iterator = dataset.make_initializable_iterator()
- next_element = iterator.get_next()
- sess.run(iterator.initializer, feed_dict={features_placeholder: np.array(X_train),
- labels_placeholder: np.array(y_train)})
- X_train = X[train_idx]
- y_train = y[train_idx]
- X_dev = X[dev_idx]
- y_dev = y[dev_idx]
- tf.reset_default_graph()
- with tf.Session() as sess:
- features_placeholder = tf.placeholder(tf.int32, [None, None], name='input_x')
- labels_placeholder = tf.placeholder(tf.int32, [None, num_classes], name='input_y')
- dataset = tf.data.Dataset.from_tensor_slices((features_placeholder, labels_placeholder))
- dataset = dataset.shuffle(buffer_size=len(train_idx))
- dataset = dataset.padded_batch(batch_size, padded_shapes=([None], [None]), padding_values=(1, 0))
- iterator = dataset.make_initializable_iterator()
- next_element = iterator.get_next()
- sess.run(iterator.initializer, feed_dict={features_placeholder: np.array(X_train),
- labels_placeholder: np.array(y_train)})
- ValueError Traceback (most recent call last)
- in ()
- ----> 1 cnn.train2(X_idx, y_bin, n_splits=5)
- in train2(self, X, y, n_splits)
- 480
- 481 self.session.run(iterator.initializer, feed_dict={features_placeholder: np.array(X_train),
- --> 482 labels_placeholder: np.array(y_train)})
- 483 # self.session.run(iterator.initializer)
- 484
- ~/.virtualenvs/ravenclaw/lib/python3.6/site-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
- 887 try:
- 888 result = self._run(None, fetches, feed_dict, options_ptr,
- --> 889 run_metadata_ptr)
- 890 if run_metadata:
- 891 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
- ~/.virtualenvs/ravenclaw/lib/python3.6/site-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
- 1087 feed_handles[subfeed_t] = subfeed_val
- 1088 else:
- -> 1089 np_val = np.asarray(subfeed_val, dtype=subfeed_dtype)
- 1090
- 1091 if (not is_tensor_handle_feed and
- ~/.virtualenvs/ravenclaw/lib/python3.6/site-packages/numpy/core/numeric.py in asarray(a, dtype, order)
- 490
- 491 """
- --> 492 return array(a, dtype, copy=False, order=order)
- 493
- 494
- ValueError: setting an array element with a sequence.
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