| /external/tensorflow/tensorflow/compiler/tests/ |
| lstm.py | 30 from tensorflow.python.ops import math_ops
37 return math_ops.maximum(math_ops.minimum(x, 1.), -1.)
65 xmw = math_ops.matmul(xm, weights)
71 in_value = math_ops.tanh(in_value)
72 in_gate = math_ops.sigmoid(in_gate)
73 forget_gate = math_ops.sigmoid(forget_gate)
74 out_gate = math_ops.sigmoid(out_gate)
|
| /external/tensorflow/tensorflow/contrib/quantization/python/ |
| __init__.py | 23 from tensorflow.contrib.quantization.python.math_ops import *
|
| /external/tensorflow/tensorflow/contrib/signal/python/ops/ |
| mel_ops.py | 25 from tensorflow.python.ops import math_ops
46 math_ops.exp(mel_values / _MEL_HIGH_FREQUENCY_Q) - 1.0
63 return _MEL_HIGH_FREQUENCY_Q * math_ops.log(
168 linear_frequencies = math_ops.linspace(
178 math_ops.linspace(_hertz_to_mel(lower_edge_hertz),
195 mel_weights_matrix = math_ops.maximum(
196 zero_float64, math_ops.minimum(lower_slopes, upper_slopes))
203 return math_ops.cast(mel_weights_matrix, dtype, name=name)
|
| mfcc_ops.py | 24 from tensorflow.python.ops import math_ops
108 return dct2 * math_ops.rsqrt(math_ops.to_float(num_mel_bins) * 2.0)
|
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| control_flow_ops_py_test.py | 55 from tensorflow.python.ops import math_ops
119 c = lambda i, s: math_ops.less(i, 10)
120 b = lambda i, s: [math_ops.add(i, 1), math_ops.add(i, s)]
170 mul_op = math_ops.multiply(enter_data, enter_five)
221 less_op = math_ops.less(zero, one)
234 add_op = math_ops.add(switch_op[0], one)
247 add_op = math_ops.add(switch_op[0], one)
249 mul_op = math_ops.multiply(switch_op[1], five)
285 less_op = math_ops.less(merge_i, enter_n
[all...] |
| segment_reduction_ops_test.py | 30 from tensorflow.python.ops import math_ops
94 ops_list = [(np.add, None, math_ops.segment_sum), (self._mean_cum_op,
96 math_ops.segment_mean),
97 (np.ndarray.__mul__, None, math_ops.segment_prod),
98 (np.minimum, None, math_ops.segment_min),
99 (np.maximum, None, math_ops.segment_max)]
102 complex_ops_list = [(np.add, None, math_ops.segment_sum),
103 (np.ndarray.__mul__, None, math_ops.segment_prod)]
132 math_ops.segment_sum(data=tf_x, segment_ids=indices)
140 s = math_ops.segment_sum(data=tf_x, segment_ids=indices
[all...] |
| gradient_correctness_test.py | 26 from tensorflow.python.ops import math_ops
35 yexp = math_ops.exp(x)
36 yexplog = math_ops.log(yexp)
|
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| target_column.py | 29 from tensorflow.python.ops import math_ops
188 math_ops.to_float(features[self._weight_column_name]), shape=(-1,))
197 weighted_loss = math_ops.multiply(unweighted_loss,
228 return math_ops.reduce_mean(loss_unweighted, name=name)
230 return math_ops.reduce_mean(loss_weighted, name=name)
253 return math_ops.reduce_mean(loss_unweighted, name="loss")
255 return math_ops.div(math_ops.reduce_sum(loss_weighted),
256 math_ops.to_float(math_ops.reduce_sum(weight_tensor))
[all...] |
| /external/tensorflow/tensorflow/contrib/py2tf/converters/ |
| logical_expressions_test.py | 23 from tensorflow.python.ops import math_ops
37 with self.compiled(node, math_ops.equal) as result:
50 with self.compiled(node, math_ops.logical_or,
51 math_ops.logical_and) as result:
|
| /external/tensorflow/tensorflow/python/grappler/ |
| model_analyzer_test.py | 25 from tensorflow.python.ops import math_ops
35 c = math_ops.add(a, b, name="c")
36 d = math_ops.add_n([a, c], name="d")
56 c = math_ops.add(a, b, name="c")
|
| tf_optimizer_test.py | 26 from tensorflow.python.ops import math_ops
36 c = math_ops.add_n([a, b], name='c')
37 d = math_ops.add_n([b, c], name='d')
|
| /external/tensorflow/tensorflow/python/ops/distributions/ |
| beta.py | 30 from tensorflow.python.ops import math_ops
232 return math_ops.exp(self._log_prob(x))
236 return math_ops.log(self._cdf(x))
240 return math_ops.betainc(self.concentration1, self.concentration0, x)
244 return ((self.concentration1 - 1.) * math_ops.log(x)
245 + (self.concentration0 - 1.) * math_ops.log1p(-x))
248 return (math_ops.lgamma(self.concentration1)
249 + math_ops.lgamma(self.concentration0)
250 - math_ops.lgamma(self.total_concentration))
255 - (self.concentration1 - 1.) * math_ops.digamma(self.concentration1
[all...] |
| /external/tensorflow/tensorflow/python/training/ |
| gradient_descent.py | 22 from tensorflow.python.ops import math_ops
50 math_ops.cast(self._learning_rate_tensor, var.dtype.base_dtype),
56 handle.handle, math_ops.cast(self._learning_rate_tensor,
67 math_ops.cast(self._learning_rate_tensor, var.dtype.base_dtype),
|
| server_lib_same_variables_no_clear_test.py | 23 from tensorflow.python.ops import math_ops
42 v2 = math_ops.matmul(v0, v1)
49 new_v2 = math_ops.matmul(new_v0, new_v1)
|
| /external/tensorflow/tensorflow/contrib/bayesflow/python/kernel_tests/ |
| halton_sequence_test.py | 27 from tensorflow.python.ops import math_ops
51 indices = math_ops.range(10, dtype=dtypes.int32)
92 f=math_ops.square, log_p=p.log_prob, sampling_dist_q=q, z=q_sample,
95 stddev = math_ops.sqrt(e_x2 - math_ops.square(e_x))
110 powers = math_ops.range(1.0, limit=dim + 1)
111 integral = math_ops.reduce_mean(
112 math_ops.reduce_prod(sample ** powers, axis=-1))
113 true_value = 1.0 / math_ops.reduce_prod(powers + 1.0)
121 sample_indices = math_ops.range(start=1000, limit=1000 + num_samples
[all...] |
| /external/tensorflow/tensorflow/contrib/bayesflow/python/ops/ |
| sgld_optimizer.py | 24 from tensorflow.python.ops import math_ops
168 self._update_momentum(rms, grad, math_ops.cast(self._decay_tensor,
174 math_ops.cast(self._learning_rate_tensor, var.dtype.base_dtype),
182 self._update_momentum(rms, grad, math_ops.cast(self._decay_tensor,
188 math_ops.cast(self._learning_rate_tensor, var.dtype.base_dtype),
206 math_ops.cast(math_ops.rsqrt(self._learning_rate), grad.dtype),
209 preconditioner = math_ops.rsqrt(
210 mom + math_ops.cast(self._diagonal_bias, grad.dtype))
212 0.5 * preconditioner * grad * math_ops.cast(self._num_pseudo_batches
[all...] |
| /external/tensorflow/tensorflow/contrib/boosted_trees/estimator_batch/ |
| custom_loss_head.py | 24 from tensorflow.python.ops import math_ops
58 average_loss = math_ops.reduce_mean(weighted_loss)
59 return average_loss, average_loss / math_ops.reduce_mean(weight_tensor)
|
| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| geometric.py | 29 from tensorflow.python.ops import math_ops
143 return math_ops.floor(
144 math_ops.log(sampled) / math_ops.log1p(-self.probs))
152 x = math_ops.floor(x)
157 -math_ops.expm1((1. + x) * math_ops.log1p(-self.probs)))
164 x = math_ops.floor(x)
168 math_ops.equal(x, 0.),
171 return x * math_ops.log1p(-safe_domain) + math_ops.log(probs
[all...] |
| sample_stats.py | 29 from tensorflow.python.ops import math_ops
129 x_rotated -= math_ops.reduce_mean(x_rotated, axis=-1, keepdims=True)
139 x_len_float64 = math_ops.cast(x_len, np.float64)
140 target_length = math_ops.pow(
142 math_ops.ceil(math_ops.log(x_len_float64 * 2) / np.log(2.)))
143 pad_length = math_ops.cast(target_length - x_len_float64, np.int32)
155 x_rotated_pad = math_ops.complex(x_rotated_pad,
160 spectral_density = fft_x_rotated_pad * math_ops.conj(fft_x_rotated_pad)
166 shifted_product = math_ops.cast(shifted_product, dtype
[all...] |
| /external/tensorflow/tensorflow/contrib/labeled_tensor/python/ops/ |
| core.py | 43 from tensorflow.python.ops import math_ops
[all...] |
| /external/tensorflow/tensorflow/contrib/metrics/python/ops/ |
| histogram_ops.py | 34 from tensorflow.python.ops import math_ops
112 math_ops.equal(1, array_ops.rank(boolean_labels)),
117 math_ops.equal(1, array_ops.rank(scores)),
141 array_ops.boolean_mask(scores, math_ops.logical_not(boolean_labels)),
200 normed_hist_true = math_ops.truediv(hist_true_acc,
201 math_ops.reduce_sum(hist_true_acc))
202 normed_hist_false = math_ops.truediv(hist_false_acc,
203 math_ops.reduce_sum(hist_false_acc))
210 delta_y_t = math_ops.cast(delta_y_t, dtypes.float32)
211 delta_x_t = math_ops.cast(delta_x_t, dtypes.float32
[all...] |
| /external/tensorflow/tensorflow/python/data/kernel_tests/ |
| filter_dataset_op_test.py | 28 from tensorflow.python.ops import math_ops
45 return math_ops.square(x), math_ops.square(y), math_ops.square(z)
50 .filter(lambda x, _y, _z: math_ops.equal(math_ops.mod(x, modulus), 0))
79 lambda x: math_ops.not_equal(math_ops.mod(x, 3), 2))
91 .filter(lambda d: math_ops.equal(d["bar"] % 2, 0))
112 summed = math_ops.reduce_sum(squared_xs
[all...] |
| /external/tensorflow/tensorflow/python/ops/ |
| confusion_matrix.py | 32 from tensorflow.python.ops import math_ops
85 math_ops.equal(expected_rank_diff + 1, rank_diff),
91 math_ops.equal(expected_rank_diff - 1, rank_diff),
156 predictions = math_ops.cast(predictions, dtypes.int64)
157 labels = math_ops.cast(labels, dtypes.int64)
170 num_classes = math_ops.maximum(math_ops.reduce_max(predictions),
171 math_ops.reduce_max(labels)) + 1
173 num_classes_int64 = math_ops.cast(num_classes, dtypes.int64)
186 weights = math_ops.cast(weights, dtype
[all...] |
| embedding_ops.py | 31 from tensorflow.python.ops import math_ops
99 else math_ops.range(ids_rank, params_rank)))
162 original_indices = math_ops.range(array_ops.size(flat_ids))
185 num_total_ids = math_ops.reduce_sum(
186 math_ops.cast(array_ops.stack(dim_0_sizes), flat_ids.dtype))
190 p_assignments = math_ops.maximum(
204 p_assignments = math_ops.cast(p_assignments, dtypes.int32)
436 segment_ids = math_ops.cast(segment_ids, dtypes.int32)
449 weights = math_ops.cast(weights, embeddings.dtype)
470 embeddings = math_ops.segment_sum(embeddings, segment_ids, name=name
[all...] |
| /external/tensorflow/tensorflow/python/ops/losses/ |
| util.py | 32 from tensorflow.python.ops import math_ops
88 return math_ops.add_n(losses, name=name)
117 return math_ops.add_n(losses, name=name)
|
