[general] creation of dnn module for gemm/conv triton routines

examples/python/tensorflow/run.py

@@ -0,0 +1,20 @@
+import os
+import tensorflow as tf
+import numpy as np
+
+data_files_path = tf.resource_loader.get_data_files_path()
+library_dir = '/home/philippe/Development/triton/build/examples/python/tensorflow'
+module = tf.load_op_library(os.path.join(library_dir, 'libtf_blocksparse.so'))
+
+M, N, K = 512, 512, 512
+a = tf.placeholder(tf.float32, shape=[M, K])
+b = tf.placeholder(tf.float32, shape=[N, K])
+locks = tf.placeholder(tf.int32, shape=[4096])
+c = module.block_sparse_mat_mul(a, b, locks)
+# Run
+sess = tf.InteractiveSession()
+sess.run(tf.global_variables_initializer())
+result = sess.run([c], feed_dict = {locks: np.zeros(4096),
+									a: np.random.rand(M, K),
+									b: np.random.rand(N, K)})
+print(result)