[codegen] added fallback when tensor cores cannot be used
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@@ -6,7 +6,7 @@ data_files_path = tf.resource_loader.get_data_files_path()
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library_dir = os.path.dirname(os.path.realpath(__file__))
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module = tf.load_op_library(os.path.join(library_dir, 'libtf_blocksparse.so'))
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M, N, K = 8192, 8192, 8192
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M, N, K = 128,128,128
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a = tf.placeholder(tf.float16, shape=[M, K])
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b = tf.placeholder(tf.float16, shape=[N, K])
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locks = tf.placeholder(tf.int32, shape=[4096])
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@@ -24,16 +24,6 @@ result = sess.run([c], feed_dict = {locks: np.zeros(4096),
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a: ha,
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b: hb})[0]
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#bench = tf.test.Benchmark().run_op_benchmark(sess=sess,
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# op_or_tensor=c,
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# feed_dict={a: ha, b: hb},
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# min_iters=100)
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#print(end - start)
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#print(2*M*N*K / (end - start) * 1e-12)
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#hresult = np.dot(ha.T, hb).T
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#dif = np.abs(result - hresult)
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#print("dif: %f" % np.max(dif))
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#np.savetxt("dif.txt", dif, fmt="%5.2f")
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#np.savetxt("gpu.txt", result, fmt="%5.2f")
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#np.savetxt("cpu.txt", hresult, fmt="%5.2f")
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hresult = np.dot(ha.T, hb).T
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dif = np.abs(result - hresult)
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print("dif: %f" % np.max(dif))
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