From 0e6392e92b2d6ed65e8364dcc66b2a7a9c8cea3e Mon Sep 17 00:00:00 2001 From: Lai Wei Date: Mon, 19 Aug 2019 02:33:57 -0700 Subject: [PATCH 1/3] fix test dataset --- keras/datasets/boston_housing.py | 2 +- keras/datasets/imdb.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/keras/datasets/boston_housing.py b/keras/datasets/boston_housing.py index 6e5bfc82ca0..653d2d9c357 100644 --- a/keras/datasets/boston_housing.py +++ b/keras/datasets/boston_housing.py @@ -26,7 +26,7 @@ def load_data(path='boston_housing.npz', test_split=0.2, seed=113): path, origin='https://s3.amazonaws.com/keras-datasets/boston_housing.npz', file_hash='f553886a1f8d56431e820c5b82552d9d95cfcb96d1e678153f8839538947dff5') - with np.load(path) as f: + with np.load(path, allow_pickle=True) as f: x = f['x'] y = f['y'] diff --git a/keras/datasets/imdb.py b/keras/datasets/imdb.py index 2d5518d04ea..97d336650d4 100644 --- a/keras/datasets/imdb.py +++ b/keras/datasets/imdb.py @@ -55,7 +55,7 @@ def load_data(path='imdb.npz', num_words=None, skip_top=0, path = get_file(path, origin='https://s3.amazonaws.com/text-datasets/imdb.npz', file_hash='599dadb1135973df5b59232a0e9a887c') - with np.load(path) as f: + with np.load(path, allow_pickle=True) as f: x_train, labels_train = f['x_train'], f['y_train'] x_test, labels_test = f['x_test'], f['y_test'] From 67b867e5c29219e2914f660670cbc3184f323add Mon Sep 17 00:00:00 2001 From: Lai Wei Date: Mon, 19 Aug 2019 02:45:32 -0700 Subject: [PATCH 2/3] fix reuters --- keras/datasets/reuters.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/keras/datasets/reuters.py b/keras/datasets/reuters.py index 04fd31fb3b9..5ce64c14b3f 100644 --- a/keras/datasets/reuters.py +++ b/keras/datasets/reuters.py @@ -53,7 +53,7 @@ def load_data(path='reuters.npz', num_words=None, skip_top=0, path = get_file(path, origin='https://s3.amazonaws.com/text-datasets/reuters.npz', file_hash='87aedbeb0cb229e378797a632c1997b6') - with np.load(path) as f: + with np.load(path, allow_pickle=True) as f: xs, labels = f['x'], f['y'] np.random.seed(seed) From 4b55756247427df5bef10fdfb8e151f5593ac814 Mon Sep 17 00:00:00 2001 From: Lai Wei Date: Mon, 19 Aug 2019 02:57:12 -0700 Subject: [PATCH 3/3] fix style: --- keras/activations.py | 2 +- keras/backend/mxnet_backend.py | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/keras/activations.py b/keras/activations.py index 5e399e769b8..57df5076571 100644 --- a/keras/activations.py +++ b/keras/activations.py @@ -31,7 +31,7 @@ def softmax(x, axis=-1): e = K.exp(x - K.max(x, axis=axis, keepdims=True)) s = K.sum(e, axis=axis, keepdims=True) return e / s - elif K.backend()=='mxnet' and ndim == 0: + elif K.backend() == 'mxnet' and ndim == 0: # x dim is not inferred yet return K.softmax(x) else: diff --git a/keras/backend/mxnet_backend.py b/keras/backend/mxnet_backend.py index 9b159113c9c..f78e2ce8fb8 100644 --- a/keras/backend/mxnet_backend.py +++ b/keras/backend/mxnet_backend.py @@ -5680,8 +5680,8 @@ def _create_predict_module(self): if self._context and hasattr(self._context[0], 'device_type') and self._context[0].device_type == 'eia': # Only Prediction is Supported with EI Context self._predict_only_module = mx.mod.Module(self._pred_mxnet_symbol, data_names=self._data_names, - label_names=self._label_names, context=self._context[0], - fixed_param_names=self._fixed_weights) + label_names=self._label_names, context=self._context[0], + fixed_param_names=self._fixed_weights) else: def sym_gen(phase): return self._pred_mxnet_symbol, self._data_names, None