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/external/tensorflow/tensorflow/python/keras/
Dlosses.py68 def __call__(self, y_true, y_pred, sample_weight=None): argument
95 (y_pred, y_true, sample_weight)):
96 losses = self.call(y_true, y_pred)
117 def call(self, y_true, y_pred): argument
148 def call(self, y_true, y_pred): argument
158 return self.fn(y_true, y_pred, **self._fn_kwargs)
669 def mean_squared_error(y_true, y_pred): argument
671 y_true = math_ops.cast(y_true, y_pred.dtype)
672 return K.mean(math_ops.squared_difference(y_pred, y_true), axis=-1)
681 def mean_absolute_error(y_true, y_pred): argument
[all …]
Dlosses_test.py59 def __call__(self, y_true, y_pred, sample_weight=None): argument
60 return (self.mse_fraction * keras.losses.mse(y_true, y_pred) +
61 (1 - self.mse_fraction) * keras.losses.mae(y_true, y_pred))
145 y_true = keras.backend.variable(np.array([[0, 1, 0], [1, 0, 0]]))
147 loss = keras.backend.eval(keras.losses.categorical_hinge(y_true, y_pred))
191 y_true = constant_op.constant([[1., 9.], [2., 5.]])
194 loss = mse_obj(y_true, y_pred, sample_weight=sample_weight)
214 y_true = constant_op.constant([4, 8, 12, 8, 1, 3], shape=(2, 3))
215 loss = mse_obj(y_true, y_true)
220 y_true = constant_op.constant([1, 9, 2, -5, -2, 6], shape=(2, 3))
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Dmetrics_functional_test.py42 y_true = K.variable(np.random.randint(0, 7, (6,)))
44 self.assertEqual(K.eval(metric(y_true, y_pred)).shape, (6,))
47 y_true = K.variable([1., 0., 0., 0.])
49 print(K.eval(metric(y_true, y_pred)))
50 self.assertAllEqual(K.eval(metric(y_true, y_pred)), [0., 1., 1., 1.])
53 y_true = K.variable([[1.], [0.], [0.], [0.]])
55 print(K.eval(metric(y_true, y_pred)))
56 self.assertAllEqual(K.eval(metric(y_true, y_pred)), [0., 1., 1., 1.])
61 y_true = K.variable(np.random.random((6,)))
63 self.assertEqual(K.eval(metric(y_true, y_pred)).shape, (6,))
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Dmetrics_confusion_matrix_test.py56 y_true = constant_op.constant(((0, 1, 0, 1, 0), (0, 0, 1, 1, 1),
61 update_op = fp_obj.update_state(y_true, y_pred)
69 y_true = constant_op.constant(((0, 1, 0, 1, 0), (0, 0, 1, 1, 1),
74 result = fp_obj(y_true, y_pred, sample_weight=sample_weight)
83 y_true = constant_op.constant(((0, 1, 1, 0), (1, 0, 0, 0), (0, 0, 0, 0),
86 update_op = fp_obj.update_state(y_true, y_pred)
97 y_true = constant_op.constant(((0, 1, 1, 0), (1, 0, 0, 0), (0, 0, 0, 0),
102 result = fp_obj(y_true, y_pred, sample_weight=sample_weight)
136 y_true = constant_op.constant(((0, 1, 0, 1, 0), (0, 0, 1, 1, 1),
141 update_op = fn_obj.update_state(y_true, y_pred)
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Dmetrics_test.py469 y_true = self.l2_norm(self.np_y_true, axis)
471 self.expected_loss = np.sum(np.multiply(y_true, y_pred), axis=(axis,))
473 self.y_true = constant_op.constant(self.np_y_true)
491 loss = cosine_obj(self.y_true, self.y_pred)
501 self.y_true,
512 loss = cosine_obj(self.y_true, self.y_pred)
533 y_true = constant_op.constant(((0, 1, 0, 1, 0), (0, 0, 1, 1, 1),
538 update_op = mae_obj.update_state(y_true, y_pred)
546 y_true = constant_op.constant(((0, 1, 0, 1, 0), (0, 0, 1, 1, 1),
551 result = mae_obj(y_true, y_pred, sample_weight=sample_weight)
[all …]
Dmetrics.py479 def update_state(self, y_true, y_pred, sample_weight=None): argument
492 y_true = math_ops.cast(y_true, self._dtype)
494 y_pred, y_true, sample_weight = squeeze_or_expand_dimensions(
495 y_pred, y_true, sample_weight)
499 y_pred.shape.assert_is_compatible_with(y_true.shape)
501 math_ops.abs(y_true - y_pred), self.normalizer)
530 def update_state(self, y_true, y_pred, sample_weight=None): argument
545 y_true = math_ops.cast(y_true, self._dtype)
547 y_pred, y_true, sample_weight = squeeze_or_expand_dimensions(
548 y_pred, y_true, sample_weight)
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/external/tensorflow/tensorflow/tools/api/golden/v1/
Dtensorflow.keras.losses.pbtxt69 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
73 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
77 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
81 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
85 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
89 …argspec: "args=[\'y_true\', \'y_pred\', \'from_logits\', \'label_smoothing\'], varargs=None, keywo…
93 …argspec: "args=[\'y_true\', \'y_pred\', \'from_logits\', \'label_smoothing\'], varargs=None, keywo…
97 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
101 …argspec: "args=[\'y_true\', \'y_pred\', \'axis\'], varargs=None, keywords=None, defaults=[\'-1\'],…
105 …argspec: "args=[\'y_true\', \'y_pred\', \'axis\'], varargs=None, keywords=None, defaults=[\'-1\'],…
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Dtensorflow.keras.metrics.pbtxt149 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
153 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
157 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
161 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
165 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
169 …argspec: "args=[\'y_true\', \'y_pred\', \'threshold\'], varargs=None, keywords=None, defaults=[\'0…
173 …argspec: "args=[\'y_true\', \'y_pred\', \'from_logits\', \'label_smoothing\'], varargs=None, keywo…
177 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
181 …argspec: "args=[\'y_true\', \'y_pred\', \'from_logits\', \'label_smoothing\'], varargs=None, keywo…
185 …argspec: "args=[\'y_true\', \'y_pred\', \'axis\'], varargs=None, keywords=None, defaults=[\'-1\'],…
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Dtensorflow.keras.losses.-loss.pbtxt11 argspec: "args=[\'self\', \'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
/external/tensorflow/tensorflow/tools/api/golden/v2/
Dtensorflow.losses.pbtxt73 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
77 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
81 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
85 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
89 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
93 …argspec: "args=[\'y_true\', \'y_pred\', \'from_logits\', \'label_smoothing\'], varargs=None, keywo…
97 …argspec: "args=[\'y_true\', \'y_pred\', \'from_logits\', \'label_smoothing\'], varargs=None, keywo…
101 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
105 …argspec: "args=[\'y_true\', \'y_pred\', \'axis\'], varargs=None, keywords=None, defaults=[\'-1\'],…
117 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
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Dtensorflow.keras.losses.pbtxt73 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
77 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
81 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
85 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
89 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
93 …argspec: "args=[\'y_true\', \'y_pred\', \'from_logits\', \'label_smoothing\'], varargs=None, keywo…
97 …argspec: "args=[\'y_true\', \'y_pred\', \'from_logits\', \'label_smoothing\'], varargs=None, keywo…
101 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
105 …argspec: "args=[\'y_true\', \'y_pred\', \'axis\'], varargs=None, keywords=None, defaults=[\'-1\'],…
117 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
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Dtensorflow.keras.metrics.pbtxt149 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
153 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
157 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
161 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
165 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
169 …argspec: "args=[\'y_true\', \'y_pred\', \'threshold\'], varargs=None, keywords=None, defaults=[\'0…
173 …argspec: "args=[\'y_true\', \'y_pred\', \'from_logits\', \'label_smoothing\'], varargs=None, keywo…
177 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
181 …argspec: "args=[\'y_true\', \'y_pred\', \'from_logits\', \'label_smoothing\'], varargs=None, keywo…
193 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
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Dtensorflow.metrics.pbtxt149 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
153 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
157 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
161 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
165 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
169 …argspec: "args=[\'y_true\', \'y_pred\', \'threshold\'], varargs=None, keywords=None, defaults=[\'0…
173 …argspec: "args=[\'y_true\', \'y_pred\', \'from_logits\', \'label_smoothing\'], varargs=None, keywo…
177 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
181 …argspec: "args=[\'y_true\', \'y_pred\', \'from_logits\', \'label_smoothing\'], varargs=None, keywo…
193 argspec: "args=[\'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
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Dtensorflow.losses.-loss.pbtxt11 argspec: "args=[\'self\', \'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
Dtensorflow.keras.losses.-loss.pbtxt11 argspec: "args=[\'self\', \'y_true\', \'y_pred\'], varargs=None, keywords=None, defaults=None"
/external/tensorflow/tensorflow/python/keras/utils/
Dlosses_utils.py60 def squeeze_or_expand_dimensions(y_pred, y_true, sample_weight): argument
85 if y_true is not None:
91 y_true_shape = y_true.get_shape()
96 y_true, y_pred = confusion_matrix.remove_squeezable_dimensions(
97 y_true, y_pred)
100 rank_diff = array_ops.rank(y_pred) - array_ops.rank(y_true)
102 y_true, y_pred)
105 is_last_dim_1, squeeze_dims, lambda: (y_true, y_pred))
106 y_true, y_pred = control_flow_ops.cond(
110 return y_pred, y_true, None
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Dmetrics_utils.py213 y_true, argument
263 y_true = math_ops.cast(y_true, dtype=dtypes.float32)
265 y_pred.shape.assert_is_compatible_with(y_true.shape)
293 y_pred, y_true, sample_weight = squeeze_or_expand_dimensions(
294 y_pred, y_true, sample_weight)
299 y_true = y_true[..., class_id]
309 math_ops.cast(y_true, dtype=dtypes.bool), [1, -1])
/external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/
D_sklearn.py157 def _accuracy_score(y_true, y_pred): argument
158 score = y_true == y_pred
162 def _mean_squared_error(y_true, y_pred): argument
163 if len(y_true.shape) > 1:
164 y_true = np.squeeze(y_true)
167 return np.average((y_true - y_pred)**2)
/external/tensorflow/tensorflow/python/keras/engine/
Dtraining_gpu_test.py47 … loss = lambda y_true, y_pred: K.sparse_categorical_crossentropy( # pylint: disable=g-long-lambda argument
48 y_true, y_pred, axis=axis)
52 loss = lambda y_true, y_pred: K.categorical_crossentropy( # pylint: disable=g-long-lambda argument
53 y_true, y_pred, axis=axis)
57 …loss = lambda y_true, y_pred: K.binary_crossentropy(y_true, y_pred) # pylint: disable=unnecessary… argument
/external/tensorflow/tensorflow/contrib/integrate/python/ops/
Dodes_test.py54 y_true = np.exp(t)
55 self.assertAllClose(y_true, y_solved)
67 y_true = np.exp(k * t)
68 self.assertAllClose(y_true, y_solved)
79 y_true = 1.0 / (2.0 - t) + t
80 self.assertAllClose(y_true, y_solved)
102 y_true = np.zeros((len(t), 2, 1))
103 y_true[:, 0, 0] = np.sin(4.0 * t) * np.exp(3.0 * t)
104 y_true[:, 1, 0] = np.cos(4.0 * t) * np.exp(3.0 * t)
105 self.assertAllClose(y_true, y_solved, atol=1e-5)
/external/libopus/scripts/
Ddump_rnn.py32 def binary_crossentrop2(y_true, y_pred): argument
33 return K.mean(2*K.abs(y_true-0.5) * K.binary_crossentropy(y_pred, y_true), axis=-1)
Drnn_train.py19 def binary_crossentrop2(y_true, y_pred): argument
20 return K.mean(2*K.abs(y_true-0.5) * K.binary_crossentropy(y_pred, y_true), axis=-1)
/external/tensorflow/tensorflow/contrib/seq2seq/python/ops/
Dloss.py160 def __call__(self, y_true, y_pred, sample_weight=None): argument
162 return sequence_loss(y_pred, y_true, sample_weight,
170 def call(self, y_true, y_pred): argument
/external/tensorflow/tensorflow/python/keras/layers/
Dlocal_test.py359 def xent(y_true, y_pred): argument
360 y_true = keras.backend.cast(
361 keras.backend.reshape(y_true, (-1,)),
365 labels=y_true,
/external/tensorflow/tensorflow/python/keras/mixed_precision/experimental/
Dkeras_test.py280 def loss_fn(y_true, y_pred): argument
281 del y_true
358 def loss_fn(y_true, y_pred): argument
359 self.assertEqual(y_true.dtype, dtypes.float32)

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