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//*****************************************************************************
// Copyright 2017-2019 Intel Corporation
//
// 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.
//*****************************************************************************
#pragma once
#include <iostream>
#include <stdexcept>
#include <ngraph/ngraph.hpp>
// Make a runtime tensor for a node output
std::shared_ptr<ngraph::runtime::Tensor> make_output_tensor(
const std::shared_ptr<ngraph::runtime::Backend>& backend,
const std::shared_ptr<ngraph::Node>& node,
size_t output_pos)
{
return backend->create_tensor(
node->get_output_element_type(output_pos),
node->get_output_shape(output_pos));
}
// Initialize a tensor from a random generator
template <typename T>
void randomize(std::function<T()> rand,
const std::shared_ptr<ngraph::runtime::Tensor>& t)
{
if (t->get_element_type().bitwidth() != 8 * sizeof(T))
{
throw std::invalid_argument(
"Randomize generator size is not the same as tensor "
"element size");
}
size_t element_count = t->get_element_count();
std::vector<T> temp;
for (size_t i = 0; i < element_count; ++i)
{
temp.push_back(rand());
}
t->write(&temp[0], 0, element_count * sizeof(T));
}
// Get a scalar value from a tensor, optionally at an element offset
template <typename T>
T get_scalar(const std::shared_ptr<ngraph::runtime::Tensor>& t,
size_t element_offset = 0)
{
T result;
t->read(&result, element_offset * sizeof(T), sizeof(T));
return result;
}
// Set a scalar value in a tensor, optionally at an element offset
template <typename T>
void set_scalar(const std::shared_ptr<ngraph::runtime::Tensor>& t,
T value,
size_t element_offset = 0)
{
t->write(&value, element_offset * sizeof(T), sizeof(T));
}
// Show a shape
std::ostream& operator<<(std::ostream& s, const ngraph::Shape& shape)
{
s << "Shape{";
for (size_t i = 0; i < shape.size(); ++i)
{
s << shape.at(i);
if (i + 1 < shape.size())
{
s << ", ";
}
}
s << "}";
return s;
}
// A debug class that supports various ways to dump information about a tensor.
class TensorDumper
{
protected:
TensorDumper(const std::string& name,
const std::shared_ptr<ngraph::runtime::Tensor>& tensor)
: m_name(name)
, m_tensor(tensor)
{
}
public:
virtual ~TensorDumper() {}
const std::string& get_name() const { return m_name; }
std::shared_ptr<ngraph::runtime::Tensor> get_tensor() const
{
return m_tensor;
}
virtual std::ostream& dump(std::ostream& s) const = 0;
protected:
std::string m_name;
std::shared_ptr<ngraph::runtime::Tensor> m_tensor;
};
std::ostream& operator<<(std::ostream& s, const TensorDumper& td)
{
return td.dump(s);
}
// Show the min and max values of a tensor
class MinMax : public TensorDumper
{
public:
MinMax(const std::string& name,
const std::shared_ptr<ngraph::runtime::Tensor>& tensor)
: TensorDumper(name, tensor)
{
size_t n = m_tensor->get_element_count();
for (size_t i = 0; i < n; ++i)
{
float s = get_scalar<float>(m_tensor, i);
m_max = std::max(m_max, s);
m_min = std::min(m_min, s);
}
}
float get_min() const { return m_min; }
float get_max() const { return m_max; }
std::ostream& dump(std::ostream& s) const override
{
return s << "MinMax[" << get_name() << ":" << get_min() << ", "
<< get_max() << "]";
}
protected:
float m_min{std::numeric_limits<float>::max()};
float m_max{std::numeric_limits<float>::min()};
};
// Show the elements of a tensor
class DumpTensor : public TensorDumper
{
public:
DumpTensor(const std::string& name,
const std::shared_ptr<ngraph::runtime::Tensor>& tensor)
: TensorDumper(name, tensor)
{
}
std::ostream& dump(std::ostream& s) const override
{
std::shared_ptr<ngraph::runtime::Tensor> t{get_tensor()};
const ngraph::Shape& shape = t->get_shape();
s << "Tensor<" << get_name() << ": ";
for (size_t i = 0; i < shape.size(); ++i)
{
s << shape.at(i);
if (i + 1 < shape.size())
{
s << ", ";
}
}
size_t pos = 0;
s << ">{";
size_t rank = shape.size();
if (rank == 0)
{
s << get_scalar<float>(t, pos++);
}
else if (rank <= 2)
{
s << "[";
for (size_t i = 0; i < shape.at(0); ++i)
{
if (rank == 1)
{
s << get_scalar<float>(t, pos++);
}
else if (rank == 2)
{
s << "[";
for (size_t j = 0; j < shape.at(1); ++j)
{
s << get_scalar<float>(t, pos++);
if (j + 1 < shape.at(1))
{
s << ", ";
}
}
s << "]";
}
if (i + 1 < shape.at(0))
{
s << ", ";
}
}
s << "]";
}
s << "}";
return s;
}
};