def test_clip_number_by_value(self):
"""Test clip with float"""
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')
tensor1 = nn.clip_by_value(variable0,
max_value=max_value,
min_value=min_value)
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_clip_number_by_value(self):
"""Test clip with float"""
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')
tensor1 = nn.ops.clip_by_value(
variable0, max_value=max_value, min_value=min_value)
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_clip_input_by_value(self):
"""Test clip with Input"""
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_input = nn.Input(shape=[], dtype='float32')
max_input = nn.Input(shape=[], dtype='float32')
tensor1 = nn.ops.clip_by_value(
variable0, max_value=max_input, min_value=min_input)
session = nn.Session()
session.initialize()
val0, val1 = session.run(
outputs=[variable0, tensor1],
givens={
min_input: np.array(min_value, dtype='float32'),
max_input: np.array(max_value, dtype='float32'),
},
)
expected = np.clip(val0, a_max=max_value, a_min=min_value)
np.testing.assert_almost_equal(val1, expected)