def test_clip_variable_by_value(self):
"""Test clip with Variable"""
shape, min_value, max_value = (10, 10), 0.4, 0.6
with nn.variable_scope(self.get_scope()):
variable0 = fixture.create_random_variable(shape, dtype='float32')
min_variable = fixture.create_constant_variable(
shape=[], dtype='float32', value=min_value, name='min_var')
max_variable = fixture.create_constant_variable(
shape=[], dtype='float32', value=max_value, name='max_var')
tensor1 = nn.ops.clip_by_value(
variable0, max_value=max_variable, min_value=min_variable)
session = nn.Session()
session.initialize()
val0, val1 = session.run(
outputs=[variable0, tensor1],
)
expected = np.clip(val0, a_max=max_value, a_min=min_value)
np.testing.assert_almost_equal(val1, expected)
def test_mul_variable(self):
"""Tensor * Variable is correct elementwise"""
shape = (3, 5)
with nn.variable_scope(self.get_scope()):
tensor1 = fixture.create_ones_tensor(shape, dtype='int32')
variable = fixture.create_constant_variable(shape, dtype='int32')
tensor2 = tensor1 * variable
tensor3 = variable * tensor1
session = nn.Session()
session.initialize()
val1, val2, val3, val0 = session.run(
outputs=[tensor1, tensor2, tensor3, variable], )
np.testing.assert_equal(val1 * val0, val2)
np.testing.assert_equal(val0 * val1, val3)
def test_mul_variable(self):
"""Tensor * Variable is correct elementwise"""
shape = (3, 5)
with nn.variable_scope(self.get_scope()):
tensor1 = fixture.create_ones_tensor(shape, dtype='int32')
variable = fixture.create_constant_variable(shape, dtype='int32')
tensor2 = tensor1 * variable
tensor3 = variable * tensor1
session = nn.Session()
session.initialize()
val1, val2, val3, val0 = session.run(
outputs=[tensor1, tensor2, tensor3, variable],
)
np.testing.assert_equal(val1 * val0, val2)
np.testing.assert_equal(val0 * val1, val3)