| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | decode_jpeg_op_test.py | 44 num_iters, argument
111 for _ in xrange(num_iters):
118 num_iters = 10
122 num_iters)
124 num_iters, False, crop_window)
126 'small.jpg', parallelism, num_iters, True, crop_window)
129 iters=num_iters,
133 iters=num_iters,
137 iters=num_iters,
142 num_iters = 10
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| D | parameterized_truncated_normal_op_test.py | 243 def parameterized_vs_naive(shape, num_iters, use_gpu=False): argument
261 param_dt = timeit.timeit(lambda: sess.run(param_op), number=num_iters)
264 naive_dt = timeit.timeit(lambda: sess.run(naive_op), number=num_iters)
268 def randn_sampler_switchover(shape, num_iters, use_gpu=False): argument
310 lambda: sess.run(uniform_sampler_op), number=num_iters)
315 lambda: sess.run(randn_sampler_op), number=num_iters)
329 num_iters = 50
331 "naive TruncatedNormalOp [%d iters]") % num_iters)
336 p_dt, n_dt = parameterized_vs_naive(shape, num_iters, use_gpu)
342 iters=num_iters,
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| D | reduce_benchmark_test.py | 41 def _run(self, func, num_iters): argument
45 for _ in range(num_iters):
48 mean_us = (end - start) * 1e6 / num_iters
50 iters=num_iters,
52 extras={"examples_per_sec": num_iters / (end - start)})
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| /external/eigen/bench/tensors/ |
| D | tensor_benchmarks.h | 36 void memcpy(int num_iters) { in memcpy() argument
39 for (int iter = 0; iter < num_iters; ++iter) { in memcpy()
43 finalizeBenchmark(static_cast<int64_t>(m_) * m_ * num_iters); in memcpy()
46 void typeCasting(int num_iters) { in typeCasting() argument
60 for (int iter = 0; iter < num_iters; ++iter) { in typeCasting()
64 finalizeBenchmark(static_cast<int64_t>(m_) * k_ * num_iters); in typeCasting()
67 void random(int num_iters) { in random() argument
75 for (int iter = 0; iter < num_iters; ++iter) { in random()
79 finalizeBenchmark(static_cast<int64_t>(m_) * m_ * num_iters); in random()
82 void slicing(int num_iters) { in slicing() argument
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| /external/tensorflow/tensorflow/python/eager/ |
| D | benchmarks_test.py | 146 def _run(self, func, num_iters, execution_mode=None): argument
154 for _ in xrange(num_iters):
159 mean_us = (end - start) * 1e6 / num_iters
161 iters=num_iters,
163 extras={"examples_per_sec": num_iters / (end - start)})
239 def _benchmark_np_multiply(self, m, num_iters): argument
242 self._run(func, num_iters)
244 def _benchmark_tf_multiply(self, m, num_iters): argument
246 self._run(func, num_iters)
248 def _benchmark_tf_multiply_op(self, m, num_iters): argument
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| /external/tensorflow/tensorflow/python/data/experimental/benchmarks/ |
| D | map_defun_benchmark.py | 37 def _run(self, op, name=None, num_iters=3000): argument
42 for _ in range(num_iters):
45 mean_us = (end - start) * 1e6 / num_iters
48 iters=num_iters,
50 extras={"examples_per_sec": num_iters / (end - start)})
64 num_iters = 100000 // input_size
69 map_defun_op, "with_defun_size_%d" % input_size, num_iters=num_iters)
71 map_fn_op, "without_defun_size_%d" % input_size, num_iters=num_iters)
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| /external/tensorflow/tensorflow/python/ops/ |
| D | transpose_benchmark.py | 34 def build_graph(device, input_shape, perm, datatype, num_iters): argument
55 for _ in range(1, num_iters):
65 def _run_graph(self, device, input_shape, perm, num_iters, datatype): argument
80 outputs = build_graph(device, input_shape, perm, datatype, num_iters)
88 duration = (time.time() - start_time) / num_iters
94 str(perm).replace(" ", ""), num_iters, duration, throughput))
105 iters=num_iters,
129 num_iters = 40
132 self._run_graph("gpu", ishape, perm, num_iters, datatype)
137 self._run_graph("gpu", ishape, perm, num_iters, datatype)
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| D | matmul_benchmark.py | 71 def run_graph(self, device, n, m, k, transpose_a, transpose_b, num_iters, argument
96 for _ in range(num_iters):
100 throughput = num_items * num_iters / duration / 1e9
103 ',ta:' + str(transpose_a) + '.tb:' + str(transpose_b), num_iters,
114 iters=num_iters,
118 def run_test_gpu(self, n, m, k, transpose_a, transpose_b, dtype, num_iters): argument
120 num_iters, dtype)
122 def test_round(self, num_iters): argument
129 self.run_test_gpu(n, m, k, transpose_a, transpose_b, dtype, num_iters)
134 self.run_test_gpu(n, m, k, transpose_a, transpose_b, dtype, num_iters)
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| D | conv2d_benchmark.py | 45 padding, num_iters, warmup_iters): argument
75 for _ in range(1, num_iters):
98 strides, padding, num_iters, warmup_iters): argument
123 padding, num_iters, warmup_iters)
148 duration = (time.time() - start_time) / num_iters
153 str(strides).replace(" ", ""), padding, num_iters, duration))
168 iters=num_iters,
204 num_iters = 80
207 padding, num_iters, warmup_iters)
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| D | concat_benchmark.py | 82 num_iters): argument
108 for _ in range(num_iters):
113 num_inputs, axis, grad, duration / num_iters,
115 100 / (duration / num_iters) / 1e9))
128 iters=num_iters))
138 num_iters = [10] * len(shapes)
140 for shape, iters in zip(shapes, num_iters):
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| /external/tensorflow/tensorflow/contrib/eager/python/examples/rnn_ptb/ |
| D | rnn_ptb_graph_test.py | 65 def _report(self, label, start, num_iters, device, batch_size): argument
66 wall_time = (time.time() - start) / num_iters
71 iters=num_iters,
79 num_iters = 100
84 dtype=tf.int64)).repeat(num_iters + num_warmup)
97 for _ in range(num_iters):
99 self._report(label, start, num_iters,
119 num_iters = 100
124 dtype=tf.int64)).repeat(num_iters + num_warmup)
142 for _ in range(num_iters):
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| /external/tensorflow/tensorflow/contrib/fused_conv/python/ops/ |
| D | fused_conv2d_bias_activation_benchmark.py | 33 padding, num_iters, data_format): argument
67 for _ in range(1, num_iters):
78 padding, num_iters, data_format): argument
116 for _ in range(1, num_iters):
135 num_iters, data_format): argument
158 num_iters, data_format)
166 duration = (time.time() - start_time) / num_iters
172 num_iters, duration))
184 iters=num_iters,
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| /external/tensorflow/tensorflow/contrib/eager/python/examples/gan/ |
| D | mnist_graph_test.py | 78 def _report(self, test_name, start, num_iters, batch_size): argument
79 avg_time = (time.time() - start) / num_iters
85 iters=num_iters, wall_time=avg_time, name=name, extras=extras)
105 num_burn, num_iters = (3, 100)
117 for _ in range(num_iters):
123 self._report('train', start, num_iters, batch_size)
138 num_burn, num_iters = (30, 1000)
143 for _ in range(num_iters):
148 self._report('generate', start, num_iters, batch_size)
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| D | mnist_test.py | 45 def _report(self, test_name, start, num_iters, batch_size): argument
46 avg_time = (time.time() - start) / num_iters
52 iters=num_iters, wall_time=avg_time, name=name, extras=extras)
99 num_burn, num_iters = (30, 1000)
106 for _ in range(num_iters):
110 self._report('generate', start, num_iters, batch_size)
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| /external/tensorflow/tensorflow/contrib/eager/python/examples/densenet/ |
| D | densenet_graph_test.py | 84 def _report(self, label, start, num_iters, batch_size): argument
85 avg_time = (time.time() - start) / num_iters
90 iters=num_iters, wall_time=avg_time, name=name, extras=extras)
109 num_burn, num_iters = (3, 30)
113 for _ in range(num_iters):
115 self._report('apply', start, num_iters, batch_size)
142 (num_burn, num_iters) = (5, 10)
146 for _ in range(num_iters):
148 self._report('train', start, num_iters, batch_size)
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| D | densenet_test.py | 205 def _report(self, label, start, num_iters, device, batch_size, data_format): argument
206 avg_time = (time.time() - start) / num_iters
211 iters=num_iters, wall_time=avg_time, name=name, extras=extras)
235 num_iters = 30
244 for _ in xrange(num_iters):
248 self._report(label, start, num_iters, device, batch_size, data_format)
286 num_iters = 10
299 for _ in xrange(num_iters):
306 self._report(label, start, num_iters, device, batch_size, data_format)
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| /external/tensorflow/tensorflow/contrib/eager/python/examples/resnet50/ |
| D | resnet50_graph_test.py | 109 def _report(self, label, start, num_iters, batch_size): argument
110 avg_time = (time.time() - start) / num_iters
115 iters=num_iters, wall_time=avg_time, name=name, extras=extras)
129 num_burn, num_iters = (3, 30)
133 for _ in range(num_iters):
138 self._report('apply', start, num_iters, batch_size)
158 (num_burn, num_iters) = (5, 10)
162 for _ in range(num_iters):
164 self._report('train', start, num_iters, batch_size)
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| D | resnet50_test.py | 200 def _report(self, label, start, num_iters, device, batch_size, data_format, argument
202 avg_time = (time.time() - start) / num_iters
209 iters=num_iters, wall_time=avg_time, name=name, extras=extras)
227 num_iters = 30
236 for _ in xrange(num_iters):
240 self._report(label, start, num_iters, device, batch_size, data_format)
273 num_iters = 10
286 for _ in xrange(num_iters):
293 self._report(label, start, num_iters, device, batch_size, data_format)
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| /external/tensorflow/tensorflow/python/ops/parallel_for/ |
| D | control_flow_ops_test.py | 1079 num_iters = array_ops.placeholder(dtypes.int32)
1085 pfor = pfor_control_flow_ops.pfor(loop_fn, num_iters)
1087 sess.run(pfor, feed_dict={num_iters: 3})
1091 num_iters = 10
1097 pfor = pfor_control_flow_ops.pfor(loop_fn, num_iters)
1099 indices = [[i, j] for i in range(num_iters) for j in range(3)]
1100 values = [4, 5, 6] * num_iters
1101 dense_shapes = [num_iters, 3]
1108 num_iters = 10
1116 pfor = pfor_control_flow_ops.pfor(loop_fn, num_iters)
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| /external/tensorflow/tensorflow/contrib/factorization/python/kernel_tests/ |
| D | masked_matmul_benchmark.py | 62 def _run_graph(self, a_shape, b_shape, nnz, num_iters, sort=False, argument
98 for _ in range(num_iters):
107 avg_wall_time += (time.time() - start_time)/num_iters
124 iters=num_iters,
131 num_iters = 10
139 self._run_graph(a_shape, b_shape, nnz, num_iters, sort, transpose_a,
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| /external/libaom/libaom/test/ |
| D | hiprec_convolve_test_util.cc | 76 const int num_iters = GET_PARAM(2); in RunCheckOutput() local
99 for (i = 0; i < num_iters; ++i) { in RunCheckOutput()
122 const int num_iters = GET_PARAM(2) / 500; in RunSpeedTest() local
147 for (i = 0; i < num_iters; ++i) { in RunSpeedTest()
161 for (i = 0; i < num_iters; ++i) { in RunSpeedTest()
213 const int num_iters = GET_PARAM(2); in RunCheckOutput() local
240 for (i = 0; i < num_iters; ++i) { in RunCheckOutput()
264 const int num_iters = GET_PARAM(2) / 500; in RunSpeedTest() local
293 for (i = 0; i < num_iters; ++i) { in RunSpeedTest()
307 for (i = 0; i < num_iters; ++i) { in RunSpeedTest()
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| /external/tensorflow/tensorflow/python/data/kernel_tests/ |
| D | memory_cleanup_test.py | 47 num_iters=100000, argument
58 for _ in six.moves.range(num_iters):
83 f, num_iters=100, increase_threshold_absolute_mb=350)
102 f, num_iters=100, increase_threshold_absolute_mb=500)
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| /external/tensorflow/tensorflow/python/kernel_tests/random/ |
| D | multinomial_op_test.py | 216 def native_op_vs_composed_ops(batch_size, num_classes, num_samples, num_iters): argument
232 native_dt = timeit.timeit(lambda: sess.run(native_op), number=num_iters)
233 composed_dt = timeit.timeit(lambda: sess.run(composed_op), number=num_iters)
240 num_iters = 50
242 num_iters)
250 num_samples, num_iters)
258 iters=num_iters,
263 iters=num_iters,
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| /external/tensorflow/tensorflow/contrib/eager/python/examples/revnet/ |
| D | revnet_test.py | 222 def _report(self, label, start, num_iters, device, batch_size, data_format): argument
223 avg_time = (time.time() - start) / num_iters
228 iters=num_iters, wall_time=avg_time, name=name, extras=extras)
244 num_iters = 10
253 for _ in range(num_iters):
257 self._report(label, start, num_iters, device, batch_size, data_format)
291 num_iters = 10
303 for _ in range(num_iters):
309 self._report(label, start, num_iters, device, batch_size, data_format)
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| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| D | kmeans_test.py | 474 def _report(self, num_iters, start, end, scores): argument
477 iters=num_iters,
478 wall_time=(end - start) / num_iters,
482 def _fit(self, num_iters=10): argument
507 self._fit(num_iters=4)
515 self._fit(num_iters=4)
520 def _fit(self, num_iters=10): argument
523 for i in range(num_iters):
539 self._report(num_iters, start, time.time(), scores)
544 def _fit(self, num_iters=10): argument
[all …]
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