From 894eaec77bce9aaaa2861378585e790c808505f8 Mon Sep 17 00:00:00 2001
From: mmrahorovic <mmrahorovic@hotmail.com>
Date: Sun, 20 Feb 2022 14:30:38 +0000
Subject: [PATCH] [tests]: unit test case for MakeMaxPoolNHWC
---
.../streamline/test_maxpool_nhwc.py | 108 ++++++++++++++++++
1 file changed, 108 insertions(+)
create mode 100644 tests/transformation/streamline/test_maxpool_nhwc.py
diff --git a/tests/transformation/streamline/test_maxpool_nhwc.py b/tests/transformation/streamline/test_maxpool_nhwc.py
new file mode 100644
index 000000000..e60057798
--- /dev/null
+++ b/tests/transformation/streamline/test_maxpool_nhwc.py
@@ -0,0 +1,108 @@
+import pytest
+
+import onnx
+import onnx.helper as oh
+from onnx import TensorProto
+
+import finn.core.onnx_exec as oxe
+from finn.core.datatype import DataType
+from finn.core.modelwrapper import ModelWrapper
+from finn.custom_op.general.maxpoolnhwc import compute_pool_output_dim
+from finn.transformation.infer_shapes import InferShapes
+from finn.transformation.streamline.reorder import MakeMaxPoolNHWC
+from finn.util.basic import gen_finn_dt_tensor
+
+
+def create_maxpool(ifm_dim, ifm_ch, kernel_shape, pads, strides, ceil_mode, idt):
+ ofm_dim_h = compute_pool_output_dim(
+ ifm_dim[0], kernel_shape[0], strides[0], pads[0], ceil_mode
+ )
+ ofm_dim_w = compute_pool_output_dim(
+ ifm_dim[1], kernel_shape[1], strides[1], pads[1], ceil_mode
+ )
+ inp = oh.make_tensor_value_info(
+ "inp", TensorProto.FLOAT, [1, ifm_ch, ifm_dim[0], ifm_dim[1]]
+ )
+ outp_mp = oh.make_tensor_value_info(
+ "outp_mp", TensorProto.FLOAT, [1, ifm_ch, ofm_dim_h, ofm_dim_w]
+ )
+ outp = oh.make_tensor_value_info(
+ "outp", TensorProto.FLOAT, [1, ofm_dim_h, ofm_dim_w, ifm_ch]
+ )
+
+ maxpool_node = oh.make_node(
+ "MaxPool",
+ inputs=["inp"],
+ outputs=["out_mp"],
+ ceil_mode=ceil_mode,
+ kernel_shape=kernel_shape,
+ pads=pads,
+ strides=strides,
+ )
+
+ transpose_node = onnx.helper.make_node(
+ "Transpose",
+ inputs=["out_mp"],
+ outputs=["outp"],
+ name="Transpose1",
+ perm=[0, 2, 3, 1],
+ )
+
+ graph = oh.make_graph(
+ nodes=[maxpool_node, transpose_node],
+ name="maxpool_graph",
+ inputs=[inp],
+ outputs=[outp],
+ value_info=[outp_mp],
+ )
+
+ model = oh.make_model(graph, producer_name="maxpool_model")
+ model = ModelWrapper(model)
+ model.set_tensor_datatype("inp", idt)
+ model.set_tensor_datatype("outp", idt)
+
+ model = model.transform(InferShapes())
+
+ return model
+
+
+# input dimension
+@pytest.mark.parametrize("ifm_dim", [[8, 8], [9, 9]])
+# input channels
+@pytest.mark.parametrize("ifm_ch", [3])
+# kernel shape
+@pytest.mark.parametrize("kernel_shape", [[2, 2]])
+# padding
+@pytest.mark.parametrize("pads", [[0, 0, 0, 0], [1, 1, 1, 1]])
+# strides
+@pytest.mark.parametrize("strides", [[2, 2]])
+# ceil_mode
+@pytest.mark.parametrize("ceil_mode", [0, 1])
+# input datatype
+@pytest.mark.parametrize("idt", [DataType["INT4"]])
+def test_maxpool_nhwc(ifm_dim, ifm_ch, kernel_shape, pads, strides, ceil_mode, idt):
+ # create MaxPool node
+ maxpool_model = create_maxpool(
+ ifm_dim, ifm_ch, kernel_shape, pads, strides, ceil_mode, idt
+ )
+
+ # generate input tensor for testing
+ input_tensor = gen_finn_dt_tensor(idt, [1, ifm_ch, ifm_dim[0], ifm_dim[1]])
+ input_dict = {"inp": input_tensor}
+
+ # execute first model
+ output_dict = oxe.execute_onnx(maxpool_model, input_dict)
+ expected = output_dict["outp"]
+
+ # transform MaxPool into MaxPoolNHWC
+ maxpool_model = maxpool_model.transform(MakeMaxPoolNHWC())
+
+ # execute transformed model
+ output_node_name = maxpool_model.graph.output[0].name
+ output_dict = oxe.execute_onnx(
+ maxpool_model, input_dict, return_full_exec_context=False
+ )
+ output = output_dict[output_node_name]
+
+ # compare outputs
+ assert (expected == output).all()
--
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