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more tinkering

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Philippe Tillet
2019-07-03 19:52:31 -07:00
parent 1d88f0a36b
commit 39aa22babb
2 changed files with 42 additions and 21 deletions
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19
examples/python/tensorflow/run.py
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@@ -56,18 +56,20 @@ def blocksparse_matmul_grad(op, dy):
return (dx, dw)
def run_shift():
B, C, H, W = 1, 16, 8, 8
B, C, H, W = 1, 16, 4, 4
R, S, F = 3, 3, 16
a = tf.placeholder(tf.float32, shape=[C, H, W, B])
b = tf.placeholder(tf.float32, shape=[C, F])
#hshift_h = np.random.randint(-R//2, R//2 + 1, size=C, dtype=np.int32)
#hshift_w = np.random.randint(-S//2, R//2 + 1, size=C, dtype=np.int32)
hshift_h = 0*np.ones(C, dtype=np.int32)
hshift_w = 0*np.ones(C, dtype=np.int32)
hshift_h = np.ones(C, dtype=np.int32)
hshift_w = np.ones(C, dtype=np.int32)
c = module.shift_conv(a, b, shift_h=tf.make_tensor_proto(hshift_h), shift_w=tf.make_tensor_proto(hshift_w))
# Reference
ha = np.ones((C, H, W, B), dtype=np.int32)
hb = np.ones((C, F), dtype=np.int32)
ha = np.random.rand(C, H, W, B)
hb = np.random.rand(C, F)
#ha = np.ones((C, H, W, B), dtype=np.int32)
#hb = np.ones((C, F), dtype=np.int32)
sess = tf.InteractiveSession()
grads = tf.test.compute_gradient([a, b], [(C, H, W, B), (C, F)], c, (C, H, W, B),
extra_feed_dict={a: ha, b: hb})
@@ -75,10 +77,11 @@ def run_shift():
dw_t, dw_n = grads[1]
print(dw_t)
print(dw_n)
#print(np.max(dw_t - dw_n))
print(np.max(dw_t - dw_n))
#print(np.max(dx_t - dx_n))
np.savetxt('theoretical.dat', dw_t, fmt='%4.2f')
np.savetxt('numerical.dat', dw_n, fmt='%4.2f')
np.savetxt('diff.dat', dw_t - dw_n, fmt='%2.4f')
np.savetxt('theoretical.dat', dw_t, fmt='%2.4f')
np.savetxt('numerical.dat', dw_n, fmt='%2.4f')
# Run
sess.run(tf.global_variables_initializer())
result = sess.run([c], feed_dict = {a: ha,