[Test] add test for debug hooks

tests/brevitas/test_brevitas_debug.py

+# Copyright (c) 2020, Xilinx
+# All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+# * Redistributions of source code must retain the above copyright notice, this
+#   list of conditions and the following disclaimer.
+#
+# * Redistributions in binary form must reproduce the above copyright notice,
+#   this list of conditions and the following disclaimer in the documentation
+#   and/or other materials provided with the distribution.
+#
+# * Neither the name of FINN nor the names of its
+#   contributors may be used to endorse or promote products derived from
+#   this software without specific prior written permission.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+from pkgutil import get_data
+
+import os
+import brevitas.onnx as bo
+import numpy as np
+import onnx
+import onnx.numpy_helper as nph
+import torch
+
+import finn.core.onnx_exec as oxe
+from finn.core.modelwrapper import ModelWrapper
+from finn.transformation.fold_constants import FoldConstants
+from finn.transformation.general import RemoveStaticGraphInputs
+from finn.transformation.infer_shapes import InferShapes
+from finn.util.test import get_test_model_trained
+from finn.util.pytorch import BrevitasDebugHook
+
+
+def test_brevitas_debug():
+    finn_onnx = "test_brevitas_debug.onnx"
+    fc = get_test_model_trained("TFC", 2, 2)
+    dbg_hook = BrevitasDebugHook()
+    bo.enable_debug(fc, dbg_hook)
+    bo.export_finn_onnx(fc, (1, 1, 28, 28), finn_onnx)
+    model = ModelWrapper(finn_onnx)
+    model = model.transform(InferShapes())
+    model = model.transform(FoldConstants())
+    model = model.transform(RemoveStaticGraphInputs())
+    assert len(model.graph.input) == 1
+    assert len(model.graph.output) == 1
+    # load one of the test vectors
+    raw_i = get_data("finn", "data/onnx/mnist-conv/test_data_set_0/input_0.pb")
+    input_tensor = onnx.load_tensor_from_string(raw_i)
+    # run using FINN-based execution
+    input_dict = {"0": nph.to_array(input_tensor)}
+    output_dict = oxe.execute_onnx(model, input_dict, return_full_exec_context=True)
+    produced = output_dict[model.graph.output[0].name]
+    # run using PyTorch/Brevitas
+    input_tensor = torch.from_numpy(nph.to_array(input_tensor)).float()
+    assert input_tensor.shape == (1, 1, 28, 28)
+    # do forward pass in PyTorch/Brevitas
+    expected = fc.forward(input_tensor).detach().numpy()
+    assert np.isclose(produced, expected, atol=1e-3).all()
+    # check all tensors at debug markers
+    names_brevitas = set(dbg_hook.outputs.keys())
+    names_finn = set(output_dict.keys())
+    names_common = names_brevitas.intersection(names_finn)
+    assert len(names_common) == 8
+    for dbg_name in names_common:
+        assert (dbg_hook.outputs[dbg_name] == output_dict[dbg_name]).all()
+    os.remove(finn_onnx)