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[codegen/batchnorm] forward and backward now seemingly working

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Philippe Tillet
2019-07-09 13:03:16 -07:00
parent f74dcb7e30
commit cc41604784
3 changed files with 32 additions and 16 deletions
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14
examples/python/tensorflow/run.py
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@@ -100,7 +100,7 @@ def batch_norm_grad(op, dy, mean, var):
def run_batchnorm():
C, H, W, B = 32, 16, 16, 16
C, H, W, B = 1, 4, 4, 4
np.random.seed(0)
# Placeholders
x = tf.placeholder(tf.float32, shape=[C, H, W, B])
@@ -112,11 +112,19 @@ def run_batchnorm():
hb = np.random.rand(C)
# batchnorm
y, m, v = module.batchnorm_forward(x, g, b, eps=1e-5)
loss = np.sum(y)
# Run
sess = tf.InteractiveSession()
sess.run(tf.global_variables_initializer())
result = sess.run([y, m, v], feed_dict = {x: hx, g: hg, b: hb})
#print(result[0], result[1], result[2])
grads = tf.test.compute_gradient([x, g, b], [(C, H, W, B), (C, ), (C, )], y, (C, H, W, B),
extra_feed_dict = {x: hx, g: hg, b: hb})
dx_t, dx_n = grads[0]
dg_t, dg_n = grads[1]
db_t, db_n = grads[2]
print(np.max(np.abs(dx_t - dx_n)))
print(np.max(np.abs(dg_t - dg_n)))
print(np.max(np.abs(db_t - db_n)))
run_batchnorm()