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+/*
+ * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <nncc/core/ADT/tensor/Shape.h>
+#include <nncc/core/ADT/tensor/LexicalLayout.h>
+#include <nncc/core/ADT/tensor/IndexEnumerator.h>
+
+#include <H5Cpp.h>
+
+#include <cassert>
+#include <cmath>
+#include <cstdint>
+#include <iostream>
+#include <set>
+#include <stdexcept>
+#include <string>
+#include <vector>
+
+namespace
+{
+
+enum class ErrorCode
+{
+ CountMismatch,
+ TypeMismatch,
+ ShapeMismatch,
+ ValueMismatch,
+};
+
+template <ErrorCode EC> class ErrorDetail;
+
+// TODO Record the details
+template <> class ErrorDetail<ErrorCode::CountMismatch>
+{
+public:
+ ErrorDetail() = default;
+};
+
+// TODO Record the details
+template <> class ErrorDetail<ErrorCode::TypeMismatch>
+{
+public:
+ ErrorDetail() = default;
+};
+
+// TODO Record the details
+template <> class ErrorDetail<ErrorCode::ShapeMismatch>
+{
+public:
+ ErrorDetail() = default;
+};
+
+// TODO Record the details
+template <> class ErrorDetail<ErrorCode::ValueMismatch>
+{
+public:
+ ErrorDetail() = default;
+};
+
+struct Observer
+{
+ virtual ~Observer() = default;
+
+ virtual void notify(const ErrorDetail<ErrorCode::CountMismatch> &) = 0;
+ virtual void notify(const ErrorDetail<ErrorCode::TypeMismatch> &) = 0;
+ virtual void notify(const ErrorDetail<ErrorCode::ShapeMismatch> &) = 0;
+ virtual void notify(const ErrorDetail<ErrorCode::ValueMismatch> &) = 0;
+};
+
+class Mux final : public Observer
+{
+public:
+ Mux() = default;
+
+public:
+ void attach(Observer *o) { _observers.insert(o); }
+
+private:
+ template <ErrorCode EC> void notify_all(const ErrorDetail<EC> &e)
+ {
+ for (auto o : _observers)
+ {
+ o->notify(e);
+ }
+ }
+
+public:
+ void notify(const ErrorDetail<ErrorCode::CountMismatch> &e) final { notify_all(e); }
+ void notify(const ErrorDetail<ErrorCode::TypeMismatch> &e) final { notify_all(e); }
+ void notify(const ErrorDetail<ErrorCode::ShapeMismatch> &e) final { notify_all(e); }
+ void notify(const ErrorDetail<ErrorCode::ValueMismatch> &e) final { notify_all(e); }
+
+public:
+ std::set<Observer *> _observers;
+};
+
+class ExitcodeTracker final : public Observer
+{
+public:
+ const int &exitcode(void) const { return _exitcode; }
+
+public:
+ void notify(const ErrorDetail<ErrorCode::CountMismatch> &) { _exitcode = 1; }
+ void notify(const ErrorDetail<ErrorCode::TypeMismatch> &) { _exitcode = 1; }
+ void notify(const ErrorDetail<ErrorCode::ShapeMismatch> &) { _exitcode = 1; }
+ void notify(const ErrorDetail<ErrorCode::ValueMismatch> &) { _exitcode = 1; }
+
+public:
+ int _exitcode = 0;
+};
+
+} // namespace
+
+//
+// HDF5 helpers
+//
+namespace
+{
+
+enum class DataType
+{
+ UNKNOWN,
+ FLOAT32,
+ /* TO BE ADDED */
+};
+
+DataType to_internal_dtype(const H5::DataType &dtype)
+{
+ if (dtype == H5::PredType::IEEE_F32BE)
+ {
+ return DataType::FLOAT32;
+ }
+ return DataType::UNKNOWN;
+}
+
+using TensorShape = nncc::core::ADT::tensor::Shape;
+
+TensorShape to_internal_shape(const H5::DataSpace &dataspace)
+{
+ int rank = dataspace.getSimpleExtentNdims();
+
+ std::vector<hsize_t> dims;
+
+ dims.resize(rank, 0);
+
+ dataspace.getSimpleExtentDims(dims.data());
+
+ TensorShape res;
+
+ res.resize(rank);
+ for (int axis = 0; axis < rank; ++axis)
+ {
+ res.dim(axis) = dims[axis];
+ }
+
+ return res;
+}
+
+uint32_t element_count(const H5::DataSpace &dataspace)
+{
+ return nncc::core::ADT::tensor::num_elements(to_internal_shape(dataspace));
+}
+
+std::vector<float> as_float_vector(const H5::DataSet &dataset)
+{
+ std::vector<float> buffer;
+
+ buffer.resize(element_count(dataset.getSpace()));
+ dataset.read(buffer.data(), H5::PredType::NATIVE_FLOAT);
+
+ return buffer;
+}
+
+using LexicalLayout = nncc::core::ADT::tensor::LexicalLayout;
+using TensorIndexEnumerator = nncc::core::ADT::tensor::IndexEnumerator;
+
+} // namespace
+
+// TODO Report the details
+int entry(int argc, char **argv)
+{
+ // The current implementation works only for command-line of the following form:
+ //
+ // i5diff -d 0.001 /path/to/left.h5 /path/to/right.h5
+ //
+ // TODO Support more options
+ assert(argc == 5);
+ assert(std::string(argv[1]) == "-d");
+ assert(std::string(argv[2]) == "0.001");
+
+ H5::H5File lhs{argv[3], H5F_ACC_RDONLY};
+ H5::H5File rhs{argv[4], H5F_ACC_RDONLY};
+
+ ExitcodeTracker exitcode_tracker;
+
+ Mux mux;
+ mux.attach(&exitcode_tracker);
+
+ // Compare values
+ do
+ {
+ // NOTE The name of value group SHOULD BE aligned with nnkit HDF5 actions
+ const std::string value_grpname{"value"};
+
+ H5::Group lhs_value_grp = lhs.openGroup(value_grpname);
+ H5::Group rhs_value_grp = rhs.openGroup(value_grpname);
+
+ // Compare value count
+ int64_t value_count = -1;
+ {
+ uint32_t lhs_value_count = static_cast<uint32_t>(lhs_value_grp.getNumObjs());
+ uint32_t rhs_value_count = static_cast<uint32_t>(rhs_value_grp.getNumObjs());
+
+ if (lhs_value_count != rhs_value_count)
+ {
+ ErrorDetail<ErrorCode::CountMismatch> error{};
+ mux.notify(error);
+ break;
+ }
+
+ value_count = std::max<int64_t>(lhs_value_count, rhs_value_count);
+ }
+ assert(value_count >= 0);
+
+ // Compare each dataset
+ for (int64_t n = 0; n < value_count; ++n)
+ {
+ // NOTE The name of dataset SHOULD BE aligned with nnkit HDF5 actions
+ const std::string dataset_name = std::to_string(n);
+
+ auto lhs_dataset = lhs_value_grp.openDataSet(dataset_name);
+ auto rhs_dataset = rhs_value_grp.openDataSet(dataset_name);
+
+ auto lhs_dtype = to_internal_dtype(lhs_dataset.getDataType());
+ auto rhs_dtype = to_internal_dtype(rhs_dataset.getDataType());
+
+ // TODO Support other data types
+ assert(rhs_dtype == DataType::FLOAT32);
+ assert(lhs_dtype == DataType::FLOAT32);
+
+ if (lhs_dtype != rhs_dtype)
+ {
+ ErrorDetail<ErrorCode::TypeMismatch> error{};
+ mux.notify(error);
+ continue;
+ }
+
+ auto lhs_shape = to_internal_shape(lhs_dataset.getSpace());
+ auto rhs_shape = to_internal_shape(rhs_dataset.getSpace());
+
+ if (!(lhs_shape == rhs_shape))
+ {
+ ErrorDetail<ErrorCode::ShapeMismatch> error{};
+ mux.notify(error);
+ continue;
+ }
+
+ assert(lhs_shape == rhs_shape);
+ assert(lhs_dtype == rhs_dtype);
+ const auto &shape = lhs_shape;
+ const auto &dtype = lhs_dtype;
+
+ switch (dtype)
+ {
+ case DataType::FLOAT32:
+ {
+ auto lhs_vector = as_float_vector(lhs_dataset);
+ auto rhs_vector = as_float_vector(rhs_dataset);
+
+ assert(lhs_vector.size() == rhs_vector.size());
+
+ LexicalLayout layout;
+
+ for (TensorIndexEnumerator e{shape}; e.valid(); e.advance())
+ {
+ const auto &ind = e.current();
+ auto lhs_value = lhs_vector.at(layout.offset(shape, ind));
+ auto rhs_value = rhs_vector.at(layout.offset(shape, ind));
+
+ // TODO Abstract equality criterion
+ if (std::abs(lhs_value - rhs_value) >= 0.001f)
+ {
+ ErrorDetail<ErrorCode::ValueMismatch> error{};
+ mux.notify(error);
+ continue;
+ }
+ }
+
+ break;
+ }
+ default:
+ throw std::runtime_error{"Not supported, yet"};
+ };
+ }
+ } while (false);
+
+ // TODO Compare names (if requested)
+
+ return exitcode_tracker.exitcode();
+}
generated by cgit v1.2.3 (git 2.25.1) at 2024-05-15 19:40:27 +0000