Compute Library
 21.02
NEThresholdKernel.cpp
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25 
26 #include "arm_compute/core/Error.h"
32 
34 
35 namespace arm_compute
36 {
37 namespace
38 {
39 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const ThresholdKernelInfo &info)
40 {
41  ARM_COMPUTE_UNUSED(info);
44 
45  // Checks performed when output is configured
46  if((output != nullptr) && (output->total_size() != 0))
47  {
50  }
51 
52  return Status{};
53 }
54 
55 std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output)
56 {
57  // Configure kernel window
58  Window win = calculate_max_window(*input, Steps());
59 
60  // Output auto inizialitation if not yet initialized
61  auto_init_if_empty(*output, *input->clone());
62 
63  // NEThresholdKernel doesn't need padding so update_window_and_padding() can be skipped
64  Coordinates coord;
65  coord.set_num_dimensions(output->num_dimensions());
66  output->set_valid_region(ValidRegion(coord, output->tensor_shape()));
67 
68  return std::make_pair(Status{}, win);
69 }
70 } // namespace
71 
73  : _func(nullptr), _input(nullptr), _output(nullptr), _info()
74 {
75 }
76 
77 void NEThresholdKernel::configure(const ITensor *input, ITensor *output, const ThresholdKernelInfo &info)
78 {
79  ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
80  ARM_COMPUTE_ERROR_THROW_ON(validate(input->info(), output->info(), info));
81 
82  _input = input;
83  _output = output;
84  _info = info;
85 
86  switch(_info.type)
87  {
89  _func = &NEThresholdKernel::run_binary;
90  break;
92  _func = &NEThresholdKernel::run_range;
93  break;
94  default:
95  ARM_COMPUTE_ERROR("Thresholding type not recognized");
96  break;
97  }
98 
99  // Configure kernel window
100  auto win_config = validate_and_configure_window(input->info(), output->info());
101  ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
102  ICPPKernel::configure(win_config.second);
103 }
104 
106 {
107  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, info));
108  ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get()).first);
109 
110  return Status{};
111 }
112 
113 inline void NEThresholdKernel::run_binary(const Window &window)
114 {
115  /** Neon vector tag type. */
116  using Type = uint8_t;
118 
119  const int window_step_x = 16 / sizeof(Type);
120  const auto window_start_x = static_cast<int>(window.x().start());
121  const auto window_end_x = static_cast<int>(window.x().end());
122 
123  Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
124  win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));
125 
126  const uint8_t threshold = _info.threshold;
127  const uint8_t true_value = _info.true_value;
128  const uint8_t false_value = _info.false_value;
129 
130  const auto vthreshold = wrapper::vdup_n(threshold, ExactTagType{});
131  const auto vtrue_value = wrapper::vdup_n(true_value, ExactTagType{});
132  const auto vfalse_value = wrapper::vdup_n(false_value, ExactTagType{});
133 
134  Iterator input(_input, win_collapsed);
135  Iterator output(_output, win_collapsed);
136 
137  execute_window_loop(win_collapsed, [&](const Coordinates &)
138  {
139  const auto input_ptr = reinterpret_cast<const Type *>(input.ptr());
140  const auto output_ptr = reinterpret_cast<Type *>(output.ptr());
141 
142  int x = window_start_x;
143  for(; x <= (window_end_x - window_step_x); x += window_step_x)
144  {
145  const auto vdata = wrapper::vloadq(input_ptr + x);
146  const auto vmask = wrapper::vcgt(vdata, vthreshold);
147  wrapper::vstore(output_ptr + x, wrapper::vbsl(vmask, vtrue_value, vfalse_value));
148  }
149 
150  for(; x < window_end_x; ++x)
151  {
152  const Type data = *(reinterpret_cast<const Type *>(input_ptr + x));
153  *(output_ptr + x) = (data > threshold) ? true_value : false_value;
154  }
155  },
156  input, output);
157 }
158 
159 inline void NEThresholdKernel::run_range(const Window &window)
160 {
161  /** Neon vector tag type. */
162  using Type = uint8_t;
164 
165  const int window_step_x = 16 / sizeof(Type);
166  const auto window_start_x = static_cast<int>(window.x().start());
167  const auto window_end_x = static_cast<int>(window.x().end());
168 
169  Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
170  win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));
171 
172  const uint8_t lower_threshold = _info.threshold;
173  const uint8_t upper_threshold = _info.upper;
174  const uint8_t true_value = _info.true_value;
175  const uint8_t false_value = _info.false_value;
176 
177  const auto vlower_threshold = wrapper::vdup_n(lower_threshold, ExactTagType{});
178  const auto vupper_threshold = wrapper::vdup_n(upper_threshold, ExactTagType{});
179  const auto vtrue_value = wrapper::vdup_n(true_value, ExactTagType{});
180  const auto vfalse_value = wrapper::vdup_n(false_value, ExactTagType{});
181 
182  Iterator input(_input, win_collapsed);
183  Iterator output(_output, win_collapsed);
184 
185  execute_window_loop(win_collapsed, [&](const Coordinates &)
186  {
187  const auto input_ptr = reinterpret_cast<const Type *>(input.ptr());
188  const auto output_ptr = reinterpret_cast<Type *>(output.ptr());
189 
190  int x = window_start_x;
191  for(; x <= (window_end_x - window_step_x); x += window_step_x)
192  {
193  const auto vdata = wrapper::vloadq(input_ptr + x);
194  auto vmask = wrapper::vcle(vdata, vupper_threshold);
195  vmask = wrapper::vand(wrapper::vcge(vdata, vlower_threshold), vmask);
196  wrapper::vstore(output_ptr + x, wrapper::vbsl(vmask, vtrue_value, vfalse_value));
197  }
198 
199  for(; x < window_end_x; ++x)
200  {
201  const Type data = *(reinterpret_cast<const Type *>(input_ptr + x));
202  *(output_ptr + x) = (data <= upper_threshold && data >= lower_threshold) ? true_value : false_value;
203  }
204  },
205  input, output);
206 }
207 
208 void NEThresholdKernel::run(const Window &window, const ThreadInfo &info)
209 {
210  ARM_COMPUTE_UNUSED(info);
213  ARM_COMPUTE_ERROR_ON(_func == nullptr);
214 
215  (this->*_func)(window);
216 }
217 } // namespace arm_compute
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
#define ARM_COMPUTE_ERROR(msg)
Print the given message then throw an std::runtime_error.
Definition: Error.h:352
1 channel, 1 U8 per channel
uint8x16_t vloadq(const uint8_t *ptr)
Definition: load.h:58
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:204
#define ARM_COMPUTE_ERROR_ON(cond)
If the condition is true then an error message is printed and an exception thrown.
Definition: Error.h:466
Store the tensor&#39;s metadata.
Definition: ITensorInfo.h:40
#define ARM_COMPUTE_ERROR_THROW_ON(status)
Definition: Error.h:455
Describe one of the image&#39;s dimensions with a start, end and step.
Definition: Window.h:77
Status class.
Definition: Error.h:52
Interface for Neon tensor.
Definition: ITensor.h:36
Copyright (c) 2017-2021 Arm Limited.
typename neon_bitvector< T, BW >::tag_type neon_bitvector_tag_t
Helper type template to get the tag type of a neon vector.
Definition: traits.h:132
static constexpr size_t DimX
Alias for dimension 0 also known as X dimension.
Definition: Window.h:43
#define ARM_COMPUTE_UNUSED(...)
To avoid unused variables warnings.
Definition: Error.h:152
Window collapse_if_possible(const Window &full_window, size_t first, size_t last, bool *has_collapsed=nullptr) const
Collapse the dimensions between first and last if possible.
Definition: Window.inl:68
static Status validate(const ITensorInfo *input, const ITensorInfo *output, const ThresholdKernelInfo &info)
Static function to check if given info will lead to a valid configuration of NEThresholdKernel.
Coordinates of an item.
Definition: Coordinates.h:37
uint8x8_t vand(const uint8x8_t &a, const uint8x8_t &b)
Definition: and.h:39
bool auto_init_if_empty(ITensorInfo &info, const TensorShape &shape, int num_channels, DataType data_type, QuantizationInfo quantization_info=QuantizationInfo())
Auto initialize the tensor info (shape, number of channels and data type) if the current assignment i...
virtual std::unique_ptr< T > clone() const =0
Provide a clone of the current object of class T.
virtual ITensorInfo * info() const =0
Interface to be implemented by the child class to return the tensor&#39;s metadata.
constexpr uint8_t * ptr() const
Return a pointer to the current pixel.
Definition: Helpers.inl:139
void run(const Window &window, const ThreadInfo &info) override
Execute the kernel on the passed window.
void set(size_t dimension, const Dimension &dim)
Set the values of a given dimension.
Definition: Window.inl:49
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:941
uint8x8_t vcle(const uint8x8_t &a, const uint8x8_t &b)
Definition: cle.h:39
ScaleKernelInfo info(interpolation_policy, default_border_mode, PixelValue(), sampling_policy, false)
uint8x8_t vcgt(const uint8x8_t &a, const uint8x8_t &b)
Definition: cgt.h:39
uint8x8_t vbsl(const uint8x8_t &a, const uint8x8_t &b, const uint8x8_t &c)
Definition: bsl.h:39
NEThresholdKernel()
Default constructor.
Information about executing thread and CPU.
Definition: CPPTypes.h:235
#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(...)
Definition: Validate.h:443
static constexpr size_t DimZ
Alias for dimension 2 also known as Z dimension.
Definition: Window.h:47
#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(...)
Definition: Validate.h:545
#define ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)
Definition: Validate.h:792
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage)
Threshold with two values.
void vstore(uint8_t *ptr, uint8x8_t val)
Definition: store.h:39
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:161
uint8x8_t vdup_n(uint8_t value, traits::vector_64_tag)
Definition: dup_n.h:41
void execute_window_loop(const Window &w, L &&lambda_function, Ts &&... iterators)
Iterate through the passed window, automatically adjusting the iterators and calling the lambda_funct...
Definition: Helpers.inl:77
Includes all wrapper headers at once.
Threshold with one value.
constexpr int end() const
Return the end of the dimension.
Definition: Window.h:99
uint8x8_t vcge(const uint8x8_t &a, const uint8x8_t &b)
Definition: cge.h:39
void configure(const ITensor *input, ITensor *output, const ThresholdKernelInfo &info)
Initialise the kernel&#39;s input, output and threshold parameters.
Iterator updated by execute_window_loop for each window element.
Definition: Helpers.h:46
constexpr int start() const
Return the start of the dimension.
Definition: Window.h:94
SimpleTensor< T > threshold(const SimpleTensor< T > &src, T threshold, T false_value, T true_value, ThresholdType type, T upper)
Definition: Threshold.cpp:35
Describe a multidimensional execution window.
Definition: Window.h:39
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:205
constexpr const Dimension & x() const
Alias to access the first dimension of the window.
Definition: Window.h:145