def testEraseFirstGrad(self):
with backprop.GradientTape(persistent=True) as tape:
m = map_ops.empty_tensor_map()
k = constant_op.constant(1.0)
k2 = constant_op.constant(2.0)
v = constant_op.constant(11.0)
v2 = constant_op.constant(22.0)
tape.watch(v)
tape.watch(v2)
m = map_ops.tensor_map_insert(m, k, v)
l = map_ops.tensor_map_lookup(m, k, v.dtype)
m = map_ops.tensor_map_insert(m, k2, v2)
m, e = map_ops.tensor_map_erase(m, k, v.dtype)
l2 = map_ops.tensor_map_lookup(m, k2, v2.dtype)
self.assertAllClose(l2, v2)
self.assertAllClose(e, v)
g = tape.gradient(l * 5, v)
self.assertAllEqual(g, 5)
g2 = tape.gradient(l2 * 6, v2)
self.assertAllEqual(g2, 6)
g3 = tape.gradient(e * 7, v)
self.assertAllEqual(g3, 7)
m, e2 = map_ops.tensor_map_erase(m, k2, v2.dtype)
g4 = tape.gradient(e2 * 8, v2)
self.assertAllEqual(g4, 8)
del tape
def testTensorMapEraseFromEmptyMapFails(self):
m = map_ops.empty_tensor_map()
k = constant_op.constant(1.0)
with self.assertRaisesRegex(errors.InvalidArgumentError,
"Trying to erase non-existent item."):
m = map_ops.tensor_map_erase(m, k, dtypes.float32)
self.evaluate(m)
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 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(v2)
m = map_ops.tensor_map_insert(m, k2, v2)
m = map_ops.tensor_map_insert(m, k, v)
s = map_ops.tensor_map_size(m)
self.assertAllEqual(s, 2)
l = map_ops.tensor_map_lookup(m, k, v.dtype)
self.assertAllClose(l, v)
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 * 5, v2)
self.assertAllEqual(g, 5)
m, e = map_ops.tensor_map_erase(m, k, v2.dtype)
s = map_ops.tensor_map_size(m)
self.assertAllEqual(s, 1)
self.assertAllClose(e, v2)
g2 = tape.gradient(e * 6, v2)
self.assertAllEqual(g2, 6)
del tape
def testTensorMapErase(self): m = map_ops.empty_tensor_map() k = constant_op.constant(1.0) v = constant_op.constant(2.0) m = map_ops.tensor_map_insert(m, k, v) s = map_ops.tensor_map_size(m) self.assertAllEqual(s, 1) m = map_ops.tensor_map_erase(m, k, v.dtype) s = map_ops.tensor_map_size(m) self.assertAllEqual(s, 0)
def testTensorMapEraseMissingKeyFails(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, k2, v)
with self.assertRaisesRegex(errors.InvalidArgumentError,
"Trying to erase non-existent item."):
m, e = map_ops.tensor_map_erase(m, k, dtypes.float32)
self.evaluate(e)
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])
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)
m, e = map_ops.tensor_map_erase(m, k, v.dtype)
s = map_ops.tensor_map_size(m)
self.assertAllEqual(s, 0)
self.assertAllClose(e, v)
def testStringValue(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)
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)
l2 = map_ops.tensor_map_lookup(m, k2, v2.dtype)
self.assertAllClose(l2, v2)
m, e = map_ops.tensor_map_erase(m, k, v.dtype)
self.assertAllEqual(e, v)
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)
def testEraseInsertComposedGrad(self):
with backprop.GradientTape(persistent=True) as tape:
m = map_ops.empty_tensor_map()
k = constant_op.constant(1.0)
k2 = constant_op.constant(2.0)
v = constant_op.constant(11.0)
v2 = constant_op.constant(22.0)
tape.watch(v)
tape.watch(v2)
m = map_ops.tensor_map_insert(m, k, v)
l = map_ops.tensor_map_lookup(m, k, v.dtype)
m = map_ops.tensor_map_erase(m, k, v.dtype)
m = map_ops.tensor_map_insert(m, k2, l)
l2 = map_ops.tensor_map_lookup(m, k2, l.dtype)
g = tape.gradient(l2 * 5, v)
self.assertAllEqual(g, 5)
del tape
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)
