def testWhenSideEffect(self):
with self.session() as sess:
def f_1(x):
rand_num = 10 * random_ops.random_uniform(shape=[2, 2],
minval=1,
maxval=9,
dtype=dtypes.int32,
name="namef1")
return rand_num * x
def f_cond(x1, z):
cond_1 = control_flow_ops.cond(math_ops.less(z[0], z[1]),
lambda: f_1(x1),
lambda: f_1(x1))
return cond_1
with ops.device('cpu'):
x1 = array_ops.placeholder(dtypes.int32, [2, 2])
z = array_ops.placeholder(dtypes.int32, [2])
with ipu.scopes.ipu_scope("/device:IPU:0"):
r1 = ipu.ipu_compiler.compile(f_cond, inputs=[x1, z])
i_x1 = np.full((2, 2), 10)
i_z = np.full((2), 8)
report = ReportJSON(self, sess)
sess.run(r1, {x1: i_x1, z: i_z})
report.parse_log()
report.assert_compute_sets_matches(
'*namef1*', 2,
"f1 should be on the list twice as it should not be cashed "
"due to SideEffect.")
def testSimpleCaching(self):
with self.session() as sess:
def f_1(x):
return math_ops.square(x, name="namef1")
def f_cond(x1, z):
cond_1 = control_flow_ops.cond(math_ops.less(z[0], z[1]),
lambda: f_1(x1),
lambda: f_1(x1))
return cond_1
with ops.device('cpu'):
x1 = array_ops.placeholder(dtypes.int32, [2, 2])
z = array_ops.placeholder(dtypes.int32, [2])
with ipu.scopes.ipu_scope("/device:IPU:0"):
r1 = ipu.ipu_compiler.compile(f_cond, inputs=[x1, z])
i_x1 = np.full((2, 2), 10)
i_z = np.full((2), 8)
report = ReportJSON(self, sess)
sess.run(r1, {x1: i_x1, z: i_z})
report.parse_log()
report.assert_compute_sets_matches(
'*namef1*', 1, "There should be only one f_1 due to cash.")
def testGRUNotCached(self):
with self.session() as sess:
# Note here the second GRU is larger.
pinputs1 = array_ops.placeholder(dataType,
[seq_len, batch_size, input_size],
name="inputs1")
pinputs2 = array_ops.placeholder(dataType,
[seq_len * 2, batch_size, input_size],
name="inputs2")
plabels = array_ops.placeholder(np.int32, [batch_size], name="labels")
with ops.device("/device:IPU:0"):
def gru_layer(inputs, name):
initial_state = _get_variable(
"initial_state",
shape=[batch_size, num_channels],
initializer=init_ops.constant_initializer(0.1, dataType))
return self._GRULayer(inputs=inputs,
weights_value=1.,
initial_state=initial_state,
training=True,
name=name)
with variable_scope.variable_scope("gru_layer1", use_resource=True):
logits1 = gru_layer(pinputs1, "layer1")
with variable_scope.variable_scope("gru_layer2", use_resource=True):
logits2 = gru_layer(pinputs2, "layer2")
logits = (math_ops.reduce_mean(logits1, axis=0) +
math_ops.reduce_mean(logits2, axis=0))
softmax = nn.sparse_softmax_cross_entropy_with_logits_v2(
logits=logits, labels=array_ops.stop_gradient(plabels))
loss = math_ops.reduce_mean(softmax)
train = gradient_descent.GradientDescentOptimizer(0.01).minimize(loss)
report = ReportJSON(self, sess)
sess.run(variables.global_variables_initializer())
report.reset()
sess.run(
[loss, train], {
pinputs1: _createGRUInput(0.5, batch_size, seq_len, input_size),
pinputs2: _createGRUInput(1.5, batch_size, seq_len * 2,
input_size),
plabels: np.ones(shape=[batch_size], dtype=np.int32),
})
report.parse_log()
report.assert_compute_sets_matches(
'*BasicGruCell/ProcessUnits/Weight/Conv*/Convolve', 4,
"There should be four fwd GRUs")
report.assert_compute_sets_matches('*/MulOGate/Op/Multiply', 2,
"There should be two bwd GRUs")
def testSameFunctions(self):
# f_1, f_2 are the same
with self.session() as sess:
def f_1(x):
return math_ops.square(x, name="namef1")
def f_2(x):
return math_ops.square(x, name="namef2")
def f_cond(x1):
cond_1 = control_flow_ops.cond(math_ops.less(1, 0),
lambda: f_1(x1),
lambda: f_1(x1))
cond_2 = control_flow_ops.cond(math_ops.less(1, 0),
lambda: f_2(x1),
lambda: f_2(x1))
return cond_1 + cond_2
with ops.device('cpu'):
x1 = array_ops.placeholder(dtypes.int32, [2, 2])
with ipu.scopes.ipu_scope("/device:IPU:0"):
r1 = ipu.ipu_compiler.compile(f_cond, inputs=[x1])
i_x1 = np.full((2, 2), 10)
report = ReportJSON(self, sess)
sess.run(r1, {x1: i_x1})
report.parse_log()
report.assert_compute_sets_matches(
'*namef1*', 1, "There should be only one f_1 due to cash.")
report.assert_compute_sets_matches(
'*namef2*', 0,
"There should not be f_2, as it is the same as f_1, due to cash."
)
