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Adding CI check for batch_nom #2168

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47fd968
Adding CI check for batchnor
szaman19 Jan 11, 2023
3d1068d
Updating batchnorm CI. Still failing
szaman19 Jan 26, 2023
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48 changes: 46 additions & 2 deletions ci_test/unit_tests/test_unit_layer_batch_normalization.py
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Original file line number Diff line number Diff line change
Expand Up @@ -104,18 +104,62 @@ def construct_model(lbann):
# LBANN implementation
decay = 0.9
epsilon = 1e-5
x = x_lbann
x = lbann.Identity(x_lbann, name='input_layer')
y = lbann.BatchNormalization(x,
decay=decay,
epsilon=epsilon,
scale_init=0.8,
bias_init=-0.25,
statistics_group_size=-1,
data_layout='data_parallel')
data_layout='data_parallel',
name="global_bn_layer")
z = lbann.L2Norm2(y)
obj.append(z)
metrics.append(lbann.Metric(z, name='global statistics'))

# NumPy Implementation

vals = []
mb_size = num_samples() // 2
i = 0
running_mean = 0
running_var = 1
scale = 0.8
bias = -0.25

while (i < num_samples()):
k = i + mb_size if (i + mb_size) < num_samples() else num_samples()
sample = _samples[i:k].reshape((k-i,7,5,3))

local_mean = sample.mean((0, 2, 3))
local_var = sample.var((0, 2, 3))

running_mean = decay * running_mean + (1-decay)*local_mean[None,:,None,None]
running_var = decay * running_var + (1-decay)*local_var[None,:,None,None]

inv_stdev = 1 / (np.sqrt(running_var + epsilon))

normalized = (sample - running_mean) * inv_stdev
y = scale * normalized + bias
z = tools.numpy_l2norm2(y)
vals.append(z)
i += mb_size
val = np.mean(z)

tol = 8 * val * np.finfo(np.float32).eps
callbacks.append(lbann.CallbackDumpOutputs(
layers="input_layer"
))
callbacks.append(lbann.CallbackDumpOutputs(
layers="global_bn_layer"
))
callbacks.append(lbann.CallbackCheckMetric(
metric=metrics[-1].name,
lower_bound=val-tol,
upper_bound=val+tol,
error_on_failure=True,
execution_modes='test'))

# ------------------------------------------
# Gradient checking
# ------------------------------------------
Expand Down