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"""Tests for tensorflow.ops.tf.matmul."""
import tensorflow.python.platform
import numpy as np
import tensorflow as tf
from tensorflow.python.kernel_tests import gradient_checker as gc
def RandMatrix(rows, cols, tr):
if tr:
rows, cols = cols, rows
return (np.clip(np.random.uniform(low=-100.0, high=100.0, size=rows * cols),
0, 100) / 100).reshape([rows, cols]).astype(np.float32)
class SparseMatMulTest(tf.test.TestCase):
def _testCpuMatmul(self, x, y, tr_a=False, tr_b=False,
sp_a=True, sp_b=False):
x_mat = np.matrix(x)
if tr_a:
x_mat = np.transpose(x_mat)
y_mat = np.matrix(y)
if tr_b:
y_mat = np.transpose(y_mat)
np_ans = x_mat * y_mat
with self.test_session(use_gpu=False):
tf_ans = tf.matmul(x, y,
transpose_a=tr_a, transpose_b=tr_b,
a_is_sparse=sp_a,
b_is_sparse=sp_b)
out = tf_ans.eval()
self.assertAllClose(np_ans, out)
self.assertShapeEqual(np_ans, tf_ans)
def testFloatBasic(self):
x = np.arange(0., 4.).reshape([4, 1]).astype(np.float32)
y = np.arange(-1., 1.).reshape([1, 2]).astype(np.float32)
self._testCpuMatmul(x, y)
# Tests testing random sized matrices.
def testFloatRandom(self):
for _ in range(10):
for tr_a in [True, False]:
for tr_b in [True, False]:
for sp_a in [True, False]:
for sp_b in [True, False]:
n, k, m = np.random.randint(1, 100, size=3)
x = RandMatrix(n, k, tr_a)
y = RandMatrix(k, m, tr_b)
self._testCpuMatmul(x, y, tr_a, tr_b, sp_a, sp_b)
class MatMulGradientTest(tf.test.TestCase):
def _testGradients(self, tr_a, tr_b, sp_a, sp_b, name):
with self.test_session():
a = tf.constant(RandMatrix(3, 2, tr_a), dtype=tf.float32)
b = tf.constant(RandMatrix(2, 4, tr_b), dtype=tf.float32)
m = tf.matmul(a, b,
name=name,
transpose_a=tr_a,
transpose_b=tr_b,
a_is_sparse=sp_a,
b_is_sparse=sp_b)
err = (gc.ComputeGradientError(a, [2, 3] if tr_a else [3, 2], m, [3, 4]) +
gc.ComputeGradientError(b, [4, 2] if tr_b else [2, 4], m, [3, 4]))
print "sparse_matmul gradient err = ", err
self.assertLess(err, 1e-3)
def testGradientInput(self):
for tr_a in [True, False]:
for tr_b in [True, False]:
for sp_a in [True, False]:
for sp_b in [True, False]:
name = "sparse_matmul_%s_%s_%s_%s" % (tr_a, tr_b, sp_a, sp_b)
self._testGradients(tr_a, tr_b, sp_a, sp_b, name)
if __name__ == "__main__":
tf.test.main()
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