| /external/tensorflow/tensorflow/contrib/bayesflow/ |
| BUILD | 36 "//third_party/py/numpy",
46 "//third_party/py/numpy",
65 "//third_party/py/numpy",
88 "//third_party/py/numpy",
108 "//third_party/py/numpy",
127 "//third_party/py/numpy",
146 "//third_party/py/numpy",
166 "//third_party/py/numpy",
187 "//third_party/py/numpy",
207 "//third_party/py/numpy",
[all...] |
| /external/tensorflow/tensorflow/contrib/learn/python/learn/datasets/ |
| mnist.py | 23 import numpy
36 dt = numpy.dtype(numpy.uint32).newbyteorder('>')
37 return numpy.frombuffer(bytestream.read(4), dtype=dt)[0]
41 """Extract the images into a 4D uint8 numpy array [index, y, x, depth].
47 data: A 4D uint8 numpy array [index, y, x, depth].
63 data = numpy.frombuffer(buf, dtype=numpy.uint8)
71 index_offset = numpy.arange(num_labels) * num_classes
72 labels_one_hot = numpy.zeros((num_labels, num_classes)
[all...] |
| /cts/suite/audio_quality/test_description/conf/ |
| check_conf.py | 18 import numpy as np
20 from numpy import *
|
| /external/tensorflow/tensorflow/contrib/crf/ |
| BUILD | 25 "//third_party/py/numpy",
34 "//third_party/py/numpy",
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/spinn/ |
| BUILD | 13 deps = ["//third_party/py/numpy"],
34 "//third_party/py/numpy",
|
| /external/tensorflow/tensorflow/contrib/kfac/examples/ |
| BUILD | 48 "//third_party/py/numpy",
58 "//third_party/py/numpy",
|
| /external/tensorflow/tensorflow/contrib/remote_fused_graph/pylib/ |
| BUILD | 32 "//third_party/py/numpy",
48 "//third_party/py/numpy",
|
| /external/tensorflow/tensorflow/examples/image_retraining/ |
| BUILD | 24 "//third_party/py/numpy",
49 "//third_party/py/numpy",
|
| /external/tensorflow/tensorflow/tools/ci_build/remote/ |
| Dockerfile.cpu | 10 python-numpy \
21 RUN pip install --upgrade enum34 futures mock numpy six backports.weakref portpicker && \
|
| Dockerfile.gpu | 10 python-numpy \
22 enum34 futures astor gast mock numpy six \
|
| /cts/apps/CameraITS/tests/scene5/ |
| test_lens_shading_and_color_uniformity.py | 20 import numpy
41 SPB_CT_LIST = numpy.arange(spb_r, 1/2., spb_r*2)
85 img_legend_ls = numpy.copy(img_rgb)
86 img_legend_ufmt = numpy.copy(img_rgb)
98 center_y = numpy.mean(img_y[top:bottom, left:right])
99 center_r_g = numpy.mean(r_g[top:bottom, left:right])
100 center_b_g = numpy.mean(b_g[top:bottom, left:right])
123 num_sample = int(numpy.asscalar((1-spb_ct*2)/spb_r/2 + 1))
124 ct_cord_x = numpy.concatenate(
125 (numpy.arange(spb_ct, 1-spb_ct+spb_r, spb_r*2)
[all...] |
| /external/tensorflow/tensorflow/contrib/solvers/ |
| BUILD | 36 "//third_party/py/numpy",
54 "//third_party/py/numpy",
71 "//third_party/py/numpy",
88 "//third_party/py/numpy",
|
| /external/tensorflow/tensorflow/contrib/timeseries/examples/ |
| BUILD | 18 "//third_party/py/numpy",
43 "//third_party/py/numpy",
66 "//third_party/py/numpy",
93 "//third_party/py/numpy",
|
| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| api_def_FloorMod.pbtxt | 9 [here](http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html)
|
| api_def_Mod.pbtxt | 9 [here](http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html)
|
| api_def_TruncateMod.pbtxt | 9 [here](http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html)
|
| /external/tensorflow/tensorflow/contrib/periodic_resample/python/kernel_tests/ |
| periodic_resample_op_test.py | 21 import numpy
34 input_tensor = numpy.arange(12).reshape((3, 4))
35 desired_shape = numpy.array([6, None])
45 input_tensor = numpy.arange(12).reshape((3, 4))
46 desired_shape = numpy.array([5, None])
56 input_tensor = numpy.arange(2 * 2 * 4).reshape((2, 2, 4))
57 desired_shape = numpy.array([4, 4, None])
58 output_tensor = numpy.array([[[0], [2], [4], [6]], [[1], [3], [5], [7]],
74 input_tensor = numpy.arange(2 * 2 * 2 * 8).reshape((2, 2, 2, 8))
75 desired_shape = numpy.array([4, 4, 4, None]
[all...] |
| /external/tensorflow/tensorflow/tools/quantization/ |
| BUILD | 28 "//third_party/py/numpy",
46 "//third_party/py/numpy",
65 "//third_party/py/numpy",
|
| /external/tensorflow/tensorflow/python/lib/core/ |
| ndarray_tensor_bridge.h | 19 #include "tensorflow/python/lib/core/numpy.h"
29 // Destructor passed to TF_NewTensor when it reuses a numpy buffer. Stores a
34 // Actually dereferences cached numpy arrays. REQUIRES being called while
38 // Creates a numpy array with shapes specified by dim_size and dims and content
45 // Converts TF_DataType to the corresponding numpy type.
|
| /external/tensorflow/tensorflow/contrib/opt/ |
| BUILD | 46 "//third_party/py/numpy",
64 "//third_party/py/numpy",
91 "//third_party/py/numpy",
117 "//third_party/py/numpy",
135 "//third_party/py/numpy",
154 "//third_party/py/numpy",
163 "//third_party/py/numpy",
194 "//third_party/py/numpy",
212 "//third_party/py/numpy",
244 "//third_party/py/numpy",
[all...] |
| /external/tensorflow/tensorflow/python/estimator/inputs/ |
| numpy_io.py | 15 """Methods to allow dict of numpy arrays."""
23 import numpy as np
37 Caller of `input_fn` usually provides `features` (dict of numpy arrays) and
38 `target`, but the underlying feeding module expects a single dict of numpy
45 features: OrderedDict of numpy arrays
61 x: numpy array object or dict of numpy array objects. If an array,
98 """Returns input function that would feed dict of numpy arrays into the model.
101 of numpy arrays. The dict `features` has the same keys as the `x`. The dict
118 x: numpy array object or dict of numpy array objects. If an array
[all...] |
| /external/autotest/client/cros/audio/ |
| audio_analysis_unittest.py | 3 import numpy
14 numpy.random.seed(0)
75 array = numpy.random.uniform(0, 1, 1000000)
93 noise = numpy.random.standard_normal(samples) * 0.005
94 x = numpy.linspace(0.0, (samples - 1) * 1.0 / rate, samples)
95 y = (coeff_1 * numpy.sin(freq_1 * 2.0 * numpy.pi * x) +
96 coeff_2 * numpy.sin(freq_2 * 2.0 * numpy.pi * x)) + noise
135 noise = numpy.random.standard_normal(samples) * noise_amplitud
[all...] |
| /tools/test/connectivity/acts/framework/tests/ |
| audio_analysis_unittest.py | 18 import numpy
29 numpy.random.seed(0)
93 array = numpy.random.uniform(0, 1, 1000000)
110 noise = numpy.random.standard_normal(int(samples)) * 0.005
111 x = numpy.linspace(0.0, (samples - 1) * 1.0 / rate, samples)
112 y = (coeff_1 * numpy.sin(freq_1 * 2.0 * numpy.pi * x) + coeff_2 *
113 numpy.sin(freq_2 * 2.0 * numpy.pi * x)) + noise
151 noise = numpy.random.standard_normal(int(samples)) * noise_amplitud
[all...] |
| /external/tensorflow/tensorflow/contrib/factorization/ |
| BUILD | 69 "//third_party/py/numpy",
141 "//third_party/py/numpy",
170 "//third_party/py/numpy",
195 "//third_party/py/numpy",
206 "//third_party/py/numpy",
241 "//third_party/py/numpy",
253 "//third_party/py/numpy",
285 "//third_party/py/numpy",
300 "//third_party/py/numpy",
313 "//third_party/py/numpy",
[all...] |
| /external/tensorflow/tensorflow/contrib/training/ |
| BUILD | 64 "//third_party/py/numpy",
98 "//third_party/py/numpy",
121 "//third_party/py/numpy",
136 "//third_party/py/numpy",
164 "//third_party/py/numpy",
187 "//third_party/py/numpy",
229 "//third_party/py/numpy",
261 "//third_party/py/numpy",
285 "//third_party/py/numpy",
307 "//third_party/py/numpy",
[all...] |
