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[codegen/shift] substantial cleaning of triton-c shift-conv code

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Philippe Tillet
2019-07-11 16:38:58 -07:00
parent 75cf2df110
commit 207e021973
4 changed files with 191 additions and 154 deletions
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12
examples/python/tensorflow/run.py
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@@ -59,15 +59,15 @@ def blocksparse_matmul_grad(op, dy):
def run_shift():
B, C, H, W = 16, 16, 4, 4
R, S, F = 3, 3, 16
R, S, F = 3, 3, 32
stride_h, stride_w = 2, 2
np.random.seed(2)
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 = np.zeros(C, dtype=np.int32)
hshift_w = np.zeros(C, dtype=np.int32)
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 = np.zeros(C, dtype=np.int32)
#hshift_w = np.zeros(C, dtype=np.int32)
c = module.shift_conv(a, b, stride_h=stride_h, stride_w=stride_w, shift_h=tf.make_tensor_proto(hshift_h), shift_w=tf.make_tensor_proto(hshift_w))
# feed values
ha = np.random.rand(C, H, W, B)
@@ -122,8 +122,6 @@ def run_batchnorm():
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[1])
print(np.mean(hx, (1, 2, 3)))
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]