def testBatchNormalizeLayerFusedFp16(self):
with ops.device("/device:IPU:0"):
with variable_scope.variable_scope("", use_resource=True):
x = array_ops.placeholder(np.float16, [4, 64, 64, 4], name="a")
normed = layers_norm.batch_normalization(x, fused=True)
with ops.device('cpu'):
report = gen_ipu_ops.ipu_event_trace()
tu.configure_ipu_system()
with tu.ipu_session() as sess:
sess.run(report)
sess.run(variables.global_variables_initializer())
result = sess.run(normed, {x: np.zeros([4, 64, 64, 4])})
self.assertAllClose(result, np.zeros([4, 64, 64, 4]))
rep = sess.run(report)
s = tu.extract_all_strings_from_event_trace(rep)
cs = tu.get_compute_sets_from_report(s)
bl = ['*convert*/Cast*']
self.assertTrue(tu.check_compute_sets_not_in_blacklist(cs, bl))
def testBatchNormalizeFused(self):
x = array_ops.placeholder(np.float32, [4, 64, 64, 4], name="a")
with ops.device("/device:IPU:0"):
with variable_scope.variable_scope("", use_resource=True):
beta = variable_scope.get_variable(
"x",
dtype=np.float32,
shape=[4],
initializer=init_ops.constant_initializer(0.0))
gamma = variable_scope.get_variable(
"y",
dtype=np.float32,
shape=[4],
initializer=init_ops.constant_initializer(1.0))
b_mean, b_var = nn.moments(x, [0, 1, 2], name='moments')
normed = nn.fused_batch_norm(x,
gamma,
beta,
b_mean,
b_var,
is_training=False)
with ops.device('cpu'):
report = gen_ipu_ops.ipu_event_trace()
tu.configure_ipu_system()
with tu.ipu_session() as sess:
sess.run(report)
sess.run(variables.global_variables_initializer())
result, _, _ = sess.run(normed, {x: np.zeros([4, 64, 64, 4])})
self.assertAllClose(result, np.zeros([4, 64, 64, 4]))
rep = sess.run(report)
s = tu.extract_all_strings_from_event_trace(rep)
cs = tu.get_compute_sets_from_report(s)
bl = ['*convert*/Cast*']
self.assertTrue(tu.check_compute_sets_not_in_blacklist(cs, bl))