def testXnorAny(self):
"""
General matmul test with randomized inputs (random stuff in tests but whatever...)
Simulate 235 batches of 440-width input for 200 nodes (all irregular)
"""
with self.test_session():
BATCH_SIZE = 235
INPUT_WIDTH = 440
NEURONS = 200
features = tf.random_uniform(minval=-10, maxval=10, shape=[BATCH_SIZE, INPUT_WIDTH], dtype=tf.float32).eval()
weights = tf.random_uniform(minval=-10, maxval=10, shape=[INPUT_WIDTH, NEURONS], dtype=tf.float32).eval()
# binarize both using sign and cast to integer
bin_features = tf.sign(tf.sign(features) - 0.5)
bin_weights = tf.sign(tf.sign(weights) - 0.5)
# weights squeezed transed
bqt = binarize_rows(tf.transpose(bin_weights), qtype=tf.int32)
bqt2 = binarize_cols(bin_weights)
self.assertAllEqual(bqt.eval(), bqt2.eval())
xnor_result = xgemm(bin_features, bin_weights, otype=tf.float32)
tf_result = tf.matmul(bin_features, bin_weights)
self.assertAllEqual(xnor_result.eval(), tf_result.eval())
def testBSTvsBS3(self):
with self.test_session():
X = tf.random_uniform(minval=-10, maxval=10, shape=[2000, 2000], dtype=tf.float32)
X = tf.sign(tf.sign(X) - 0.5).eval()
bst = binarize_rows(X, qtype=tf.int32)
Xt = tf.transpose(X)
bst2 = binarize_cols(Xt)
self.assertAllEqual(bst.eval(), bst2.eval())
def testPythonSqueeze(self):
with self.test_session():
m = generate_matrix(200)
mm = tf.constant(m, dtype=tf.float32)
pp = tf.constant(python_binarize_rows(m)).eval()
with tf.device('gpu:0'):
mm_squeeze = binarize_rows(mm, qtype=tf.int32).eval()
self.assertAllEqual(mm_squeeze, pp)
def testBinarizeColsTranposeUnaligned(self):
with self.test_session():
M = tf.constant(
[[-1, -1, -1],
[-1, -1, 1],
[-1, 1, -1],
[-1, 1, 1],
[-1, -1, -1],
[-1, -1, 1]], dtype=tf.int32
)
bst = binarize_rows(tf.transpose(M), qtype=tf.int32)
b_squeeze = binarize_cols(M)
self.assertAllEqual(bst.eval(), b_squeeze.eval())
def testBinsqueezeA_GPU_32bit(self):
with self.test_session():
with tf.device('/gpu:0'):
a_squeeze = binarize_rows(self.A, qtype=tf.int32).eval()
self.assertAllEqual(a_squeeze, self.AC.eval())
def testBinsqueezeB_CPU(self):
with self.test_session():
with tf.device('/cpu:0'):
b_squeeze = tf.transpose(binarize_rows(tf.transpose(self.B), qtype=tf.int32))
self.assertAllEqual(b_squeeze.eval(), self.BC.eval())
def testBinsqueezeA_CPU_16bit(self):
with self.test_session():
with tf.device('/cpu:0'):
a_squeeze = binarize_rows(self.A, qtype=tf.int16).eval()
self.assertAllEqual(a_squeeze, self.AC16.eval())