arm_compute v17.09
Change-Id: I4bf8f4e6e5f84ce0d5b6f5ba570d276879f42a81
diff --git a/utils/GraphUtils.cpp b/utils/GraphUtils.cpp
new file mode 100644
index 0000000..d763606
--- /dev/null
+++ b/utils/GraphUtils.cpp
@@ -0,0 +1,165 @@
+/*
+ * Copyright (c) 2017 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+
+#include "utils/GraphUtils.h"
+#include "utils/Utils.h"
+
+#ifdef ARM_COMPUTE_CL
+#include "arm_compute/core/CL/OpenCL.h"
+#include "arm_compute/runtime/CL/CLTensor.h"
+#endif /* ARM_COMPUTE_CL */
+
+#include "arm_compute/core/Error.h"
+#include "libnpy/npy.hpp"
+
+#include <sstream>
+
+using namespace arm_compute::graph_utils;
+
+PPMWriter::PPMWriter(std::string name, unsigned int maximum)
+ : _name(std::move(name)), _iterator(0), _maximum(maximum)
+{
+}
+
+bool PPMWriter::access_tensor(ITensor &tensor)
+{
+ std::stringstream ss;
+ ss << _name << _iterator << ".ppm";
+ if(dynamic_cast<Tensor *>(&tensor) != nullptr)
+ {
+ arm_compute::utils::save_to_ppm(dynamic_cast<Tensor &>(tensor), ss.str());
+ }
+#ifdef ARM_COMPUTE_CL
+ else if(dynamic_cast<CLTensor *>(&tensor) != nullptr)
+ {
+ arm_compute::utils::save_to_ppm(dynamic_cast<CLTensor &>(tensor), ss.str());
+ }
+#endif /* ARM_COMPUTE_CL */
+
+ _iterator++;
+ if(_maximum == 0)
+ {
+ return true;
+ }
+ return _iterator < _maximum;
+}
+
+DummyAccessor::DummyAccessor(unsigned int maximum)
+ : _iterator(0), _maximum(maximum)
+{
+}
+
+bool DummyAccessor::access_tensor(ITensor &tensor)
+{
+ ARM_COMPUTE_UNUSED(tensor);
+ bool ret = _maximum == 0 || _iterator < _maximum;
+ if(_iterator == _maximum)
+ {
+ _iterator = 0;
+ }
+ else
+ {
+ _iterator++;
+ }
+ return ret;
+}
+
+NumPyBinLoader::NumPyBinLoader(std::string filename)
+ : _filename(std::move(filename))
+{
+}
+
+bool NumPyBinLoader::access_tensor(ITensor &tensor)
+{
+ const TensorShape tensor_shape = tensor.info()->tensor_shape();
+ std::vector<unsigned long> shape;
+
+ // Open file
+ std::ifstream stream(_filename, std::ios::in | std::ios::binary);
+ ARM_COMPUTE_ERROR_ON_MSG(!stream.good(), "Failed to load binary data");
+ // Check magic bytes and version number
+ unsigned char v_major = 0;
+ unsigned char v_minor = 0;
+ npy::read_magic(stream, &v_major, &v_minor);
+
+ // Read header
+ std::string header;
+ if(v_major == 1 && v_minor == 0)
+ {
+ header = npy::read_header_1_0(stream);
+ }
+ else if(v_major == 2 && v_minor == 0)
+ {
+ header = npy::read_header_2_0(stream);
+ }
+ else
+ {
+ ARM_COMPUTE_ERROR("Unsupported file format version");
+ }
+
+ // Parse header
+ bool fortran_order = false;
+ std::string typestr;
+ npy::ParseHeader(header, typestr, &fortran_order, shape);
+
+ // Check if the typestring matches the given one
+ std::string expect_typestr = arm_compute::utils::get_typestring(tensor.info()->data_type());
+ ARM_COMPUTE_ERROR_ON_MSG(typestr != expect_typestr, "Typestrings mismatch");
+
+ // Validate tensor shape
+ ARM_COMPUTE_ERROR_ON_MSG(shape.size() != tensor_shape.num_dimensions(), "Tensor ranks mismatch");
+ if(fortran_order)
+ {
+ for(size_t i = 0; i < shape.size(); ++i)
+ {
+ ARM_COMPUTE_ERROR_ON_MSG(tensor_shape[i] != shape[i], "Tensor dimensions mismatch");
+ }
+ }
+ else
+ {
+ for(size_t i = 0; i < shape.size(); ++i)
+ {
+ ARM_COMPUTE_ERROR_ON_MSG(tensor_shape[i] != shape[shape.size() - i - 1], "Tensor dimensions mismatch");
+ }
+ }
+
+ // Read data
+ if(tensor.info()->padding().empty())
+ {
+ // If tensor has no padding read directly from stream.
+ stream.read(reinterpret_cast<char *>(tensor.buffer()), tensor.info()->total_size());
+ }
+ else
+ {
+ // If tensor has padding accessing tensor elements through execution window.
+ Window window;
+ window.use_tensor_dimensions(tensor_shape);
+
+ execute_window_loop(window, [&](const Coordinates & id)
+ {
+ stream.read(reinterpret_cast<char *>(tensor.ptr_to_element(id)), tensor.info()->element_size());
+ });
+ }
+ return true;
+}