def testTensorMapHasKey(self): m = map_ops.empty_tensor_map() k = constant_op.constant(1.0) k2 = constant_op.constant(2.0) v = constant_op.constant(2.0) m = map_ops.tensor_map_insert(m, k, v) # Check has key. b = map_ops.tensor_map_has_key(m, k) b2 = map_ops.tensor_map_has_key(m, k2) self.assertAllEqual(b, True) self.assertAllEqual(b2, False)
def testStringKeyGrad(self):
with backprop.GradientTape(persistent=True) as tape:
m = map_ops.empty_tensor_map()
k = constant_op.constant("key")
k2 = constant_op.constant("key2")
v = constant_op.constant(2.0)
v2 = constant_op.constant(22.0)
tape.watch(v)
tape.watch(v2)
m = map_ops.tensor_map_insert(m, k, v)
m = map_ops.tensor_map_insert(m, k2, v2)
s = map_ops.tensor_map_size(m)
self.assertAllEqual(s, 2)
# Test lookup and gradient.
l = map_ops.tensor_map_lookup(m, k, v.dtype)
self.assertAllClose(l, v)
self.assertAllClose(tape.gradient(l * 5, v), 5)
# Test replace and gradient.
m = map_ops.tensor_map_insert(m, k, v2)
l2 = map_ops.tensor_map_lookup(m, k, v2.dtype)
self.assertAllClose(l2, v2)
g = tape.gradient(l2 * 6, v2)
self.assertAllEqual(g, 6)
# Test erase, has key, and gradient.
m = map_ops.tensor_map_erase(m, k, v2.dtype)
s = map_ops.tensor_map_size(m)
self.assertAllEqual(s, 1)
h = map_ops.tensor_map_has_key(m, k)
self.assertAllEqual(h, False)
l = map_ops.tensor_map_lookup(m, k2, v2.dtype)
g2 = tape.gradient(l * 6, v2)
self.assertAllEqual(g2, 6)
del tape
def testIfHasKeyLookup(self):
m = map_ops.empty_tensor_map()
k = constant_op.constant(1.0)
k2 = constant_op.constant(2.0)
v = constant_op.constant(2.0)
m = map_ops.tensor_map_insert(m, k, v)
default_value = array_ops.zeros_like(v)
l = control_flow_ops.cond(
map_ops.tensor_map_has_key(m, k),
lambda: map_ops.tensor_map_lookup(m, k, dtypes.float32),
lambda: default_value)
l2 = control_flow_ops.cond(
map_ops.tensor_map_has_key(m, k2),
lambda: map_ops.tensor_map_lookup(m, k, dtypes.float32),
lambda: default_value)
self.assertAllClose(l, v)
self.assertAllClose(l2, default_value)
def testStringKeyValue(self):
m = map_ops.empty_tensor_map()
k = constant_op.constant("key")
v = constant_op.constant("value")
k2 = constant_op.constant(1.0)
v2 = constant_op.constant(2.0)
# Test insert and lookup on string key-value pair.
m = map_ops.tensor_map_insert(m, k, v)
m = map_ops.tensor_map_insert(m, k2, v2)
l = map_ops.tensor_map_lookup(m, k, v.dtype)
self.assertAllEqual(l, v)
# Test lookup on float key-value pair.
l2 = map_ops.tensor_map_lookup(m, k2, v2.dtype)
self.assertAllClose(l2, v2)
# Test erase and has key.
self.assertAllEqual(map_ops.tensor_map_has_key(m, k), True)
m = map_ops.tensor_map_erase(m, k, v.dtype)
self.assertAllEqual(map_ops.tensor_map_has_key(m, k), False)
self.assertAllEqual(map_ops.tensor_map_has_key(m, k2), True)
def testVectorValue(self): m = map_ops.empty_tensor_map() k = constant_op.constant([1.0, 2.0]) v = constant_op.constant([11.0, 22.0]) # Test insert and lookup. m = map_ops.tensor_map_insert(m, k, v) s = map_ops.tensor_map_size(m) self.assertAllEqual(s, 1) l = map_ops.tensor_map_lookup(m, k, v.dtype) self.assertAllEqual(l, v) # Test erase and has key. m = map_ops.tensor_map_erase(m, k, v.dtype) s = map_ops.tensor_map_size(m) self.assertAllEqual(s, 0) self.assertAllEqual(map_ops.tensor_map_has_key(m, k), False)