from tensorflow.python.keras.optimizer_v2 import nadam
from tensorflow.python.keras.optimizer_v2 import optimizer_v2
from tensorflow.python.keras.optimizer_v2 import rmsprop
from tensorflow.python.keras.utils import np_utils
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import clip_ops
from tensorflow.python.ops import state_ops
from tensorflow.python.ops import variables
from tensorflow.python.platform import test
from tensorflow.python.training import momentum
from tensorflow.python.training import training_util
_DATA_TYPES = [dtypes.half, dtypes.float32, dtypes.float64]
# TODO(b/141710709): complex support in NVCC and ROCM.
if (not test_util.IsBuiltWithNvcc() and not test.is_built_with_rocm()):
_DATA_TYPES += [dtypes.complex64, dtypes.complex128]
class OptimizerTest(test.TestCase, parameterized.TestCase):
@combinations.generate(combinations.combine(mode=['graph', 'eager']))
def testBasic(self):
for dtype in _DATA_TYPES:
with test_util.use_gpu():
var0 = variables.Variable([1.0, 2.0], dtype=dtype)
var1 = variables.Variable([3.0, 4.0], dtype=dtype)
loss = lambda: 5 * var0 + 3 * var1 # pylint: disable=cell-var-from-loop
sgd = gradient_descent.SGD(3.0)
self.evaluate(variables.global_variables_initializer())
from tensorflow.python.eager import context
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import test_util
from tensorflow.python.keras.optimizer_v2 import learning_rate_schedule
from tensorflow.python.keras.optimizer_v2 import rmsprop
from tensorflow.python.ops import embedding_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import resource_variable_ops
from tensorflow.python.ops import variables
from tensorflow.python.platform import test
_DATA_TYPES = [dtypes.half, dtypes.float32, dtypes.float64]
# TODO(b/143684500): Eigen to support complex sqrt
if not test_util.IsBuiltWithNvcc() and platform.system() != "Windows" \
and not test.is_built_with_rocm():
_DATA_TYPES += [dtypes.complex64, dtypes.complex128]
_TEST_PARAM_VALUES = [
# learning_rate, rho, momentum, epsilon, centered
[0.05, 0.9, 0.0, 1e-3, True],
[0.05, 0.9, 0.0, 1e-3, False],
[0.1, 0.9, 0.0, 1e-3, True],
[0.01, 0.9, 0.0, 1e-5, True],
[0.01, 0.9, 0.9, 1e-5, True],
]
_TESTPARAMS = [
[data_type] + values
for data_type, values in itertools.product(_DATA_TYPES, _TEST_PARAM_VALUES)
import copy
import itertools
import math
from absl.testing import parameterized
import numpy as np
from tensorflow.python.framework import test_util
from keras import combinations
from keras import testing_utils
from keras.optimizer_v2 import learning_rate_schedule
from keras.optimizer_v2 import rmsprop
_DATA_TYPES = [tf.half, tf.float32, tf.float64]
# TODO(b/143684500): Eigen to support complex sqrt
if not test_util.IsBuiltWithNvcc():
_DATA_TYPES += [tf.complex64, tf.complex128]
_TEST_PARAM_VALUES = [
# learning_rate, rho, momentum, epsilon, centered
[0.05, 0.9, 0.0, 1e-3, True],
[0.05, 0.9, 0.0, 1e-3, False],
[0.1, 0.9, 0.0, 1e-3, True],
[0.01, 0.9, 0.0, 1e-5, True],
[0.01, 0.9, 0.9, 1e-5, True],
]
_TESTPARAMS = [
[data_type] + values
for data_type, values in itertools.product(_DATA_TYPES, _TEST_PARAM_VALUES)
]
