65 lines
2.2 KiB
Python
65 lines
2.2 KiB
Python
import os
|
|
import tensorflow as tf
|
|
import numpy as np
|
|
from time import time
|
|
data_files_path = tf.resource_loader.get_data_files_path()
|
|
library_dir = os.path.dirname(os.path.realpath(__file__))
|
|
module = tf.load_op_library(os.path.join(library_dir, 'libtf_blocksparse.so'))
|
|
|
|
def run_dot():
|
|
M, N, K = 128,128,128
|
|
a = tf.placeholder(tf.float16, shape=[M, K])
|
|
b = tf.placeholder(tf.float16, shape=[N, K])
|
|
locks = tf.placeholder(tf.int32, shape=[4096])
|
|
# c = tf.matmul(a, b, transpose_a=True)
|
|
c = module.dot(a, b, locks)
|
|
# Reference
|
|
ha = np.random.rand(M, K).astype(np.float16)
|
|
hb = np.random.rand(N, K).astype(np.float16)
|
|
# Run
|
|
sess = tf.InteractiveSession()
|
|
sess.run(tf.global_variables_initializer())
|
|
result = sess.run([c], feed_dict = {locks: np.zeros(4096),
|
|
a: ha,
|
|
b: hb})[0]
|
|
# Test
|
|
hresult = np.dot(ha.T, hb).T
|
|
dif = np.abs(result - hresult)
|
|
print("dif: %f" % np.max(dif))
|
|
|
|
def run_conv():
|
|
B, C, H, W = 16, 32, 32, 32
|
|
R, S, NF = 3, 3, 32
|
|
a = tf.placeholder(tf.float32, shape=[B, C, H, W])
|
|
b = tf.placeholder(tf.float32, shape=[C, R, S, NF])
|
|
c = module.conv2d(a, b)
|
|
# Reference
|
|
ha = np.random.rand(B, C, H, W)
|
|
hb = np.random.rand(C, R, S, NF)
|
|
# Run
|
|
sess = tf.InteractiveSession()
|
|
sess.run(tf.global_variables_initializer())
|
|
result = sess.run([c], feed_dict = {a: ha,
|
|
b: hb})[0]
|
|
|
|
def run_shift():
|
|
B, C, H, W = 16, 32, 32, 32
|
|
R, S, F = 3, 3, 32
|
|
a = tf.placeholder(tf.float32, shape=[C, H, W, B])
|
|
b = tf.placeholder(tf.float32, shape=[C, F])
|
|
shift_h = tf.zeros(C, tf.int32)
|
|
shift_w = tf.zeros(C, tf.int32)
|
|
hshift_h = np.zeros(C, np.int32)
|
|
hshift_w = np.zeros(C, 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.random.rand(C, H, W, B)
|
|
hb = np.random.rand(C, F)
|
|
# Run
|
|
sess = tf.InteractiveSession()
|
|
sess.run(tf.global_variables_initializer())
|
|
result = sess.run([c], feed_dict = {a: ha,
|
|
b: hb})[0]
|
|
|
|
run_shift()
|