crazydemo commented on code in PR #12151: URL: https://github.com/apache/tvm/pull/12151#discussion_r932899385
########## tests/python/contrib/test_dnnl.py: ########## @@ -788,6 +789,44 @@ def test_conv2d_pattern(run_module, dtype="float32"): run_and_verify_func(config, run_module=run_module, dtype=dtype) +def test_conv2d_bias_sum_relu(run_module, dtype="float32"): + x_shape = (1, 32, 8, 8) + k_shape = (16, 32, 3, 3) + + def get_conv2d_bn_sum_relu(x_shape, k_shape, sum_shape, dtype="float32"): + out, dic, param_lst = get_conv2d_bias(x_shape=x_shape, k_shape=k_shape, dtype=dtype) + beta = relay.const(np.zeros(k_shape[0]).astype(dtype)) + gamma = relay.const(np.ones(k_shape[0]).astype(dtype)) + moving_mean = relay.const(np.zeros(k_shape[0]).astype(dtype)) + moving_var = relay.const(np.ones(k_shape[0]).astype(dtype)) + out, _, _ = relay.nn.batch_norm( + out, + gamma=gamma, + beta=beta, + moving_mean=moving_mean, + moving_var=moving_var, + axis=1, + center=True, + scale=True, + epsilon=1e-5, + ) + sum_data = relay.var("data1", shape=sum_shape, dtype=dtype) + out = relay.add(out, sum_data) + dic["data1"] = sum_shape + param_lst += ["data1"] + return relay.nn.relu(out), dic, param_lst + + conv2d_bn_sum_relu, dic, param_lst = get_conv2d_bn_sum_relu(x_shape, k_shape, sum_shape=(1, 16, 6, 6), dtype=dtype) Review Comment: Fixed. ########## tests/python/contrib/test_dnnl.py: ########## @@ -788,6 +789,44 @@ def test_conv2d_pattern(run_module, dtype="float32"): run_and_verify_func(config, run_module=run_module, dtype=dtype) +def test_conv2d_bias_sum_relu(run_module, dtype="float32"): + x_shape = (1, 32, 8, 8) + k_shape = (16, 32, 3, 3) + + def get_conv2d_bn_sum_relu(x_shape, k_shape, sum_shape, dtype="float32"): + out, dic, param_lst = get_conv2d_bias(x_shape=x_shape, k_shape=k_shape, dtype=dtype) + beta = relay.const(np.zeros(k_shape[0]).astype(dtype)) + gamma = relay.const(np.ones(k_shape[0]).astype(dtype)) + moving_mean = relay.const(np.zeros(k_shape[0]).astype(dtype)) + moving_var = relay.const(np.ones(k_shape[0]).astype(dtype)) + out, _, _ = relay.nn.batch_norm( + out, + gamma=gamma, + beta=beta, + moving_mean=moving_mean, + moving_var=moving_var, + axis=1, + center=True, + scale=True, + epsilon=1e-5, + ) + sum_data = relay.var("data1", shape=sum_shape, dtype=dtype) + out = relay.add(out, sum_data) + dic["data1"] = sum_shape + param_lst += ["data1"] + return relay.nn.relu(out), dic, param_lst + + conv2d_bn_sum_relu, dic, param_lst = get_conv2d_bn_sum_relu(x_shape, k_shape, sum_shape=(1, 16, 6, 6), dtype=dtype) + conv2d_bn_sum_relu = tvm.IRModule.from_expr(conv2d_bn_sum_relu) + config = conv2d_bn_sum_relu, dic, param_lst + run_and_verify_func(config, run_module=run_module, dtype=dtype) + + conv2d_bn_sum_relu, dic, param_lst = get_conv2d_bn_sum_relu(x_shape, k_shape, sum_shape=(1, 16, 1, 1), dtype=dtype) Review Comment: Fixed. ########## tests/python/contrib/test_dnnl.py: ########## @@ -1732,4 +1771,5 @@ def generate_model(p, c): if __name__ == "__main__": - tvm.testing.main() + # tvm.testing.main() + test_conv2d_bias_sum_relu(True) Review Comment: Fixed. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: commits-unsubscr...@tvm.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org