Compute Library
 21.11
CLComparisonKernel.cpp
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25 
28 #include "src/core/CL/CLValidate.h"
31 #include "support/StringSupport.h"
32 
33 #include <map>
34 
35 namespace arm_compute
36 {
37 namespace
38 {
39 // Create supported comparisons map
40 const std::map<ComparisonOperation, std::string> supported_comparison_ops =
41 {
42  { ComparisonOperation::Equal, "EQUAL" },
43  { ComparisonOperation::NotEqual, "NOTEQUAL" },
44  { ComparisonOperation::Greater, "GREATER" },
45  { ComparisonOperation::GreaterEqual, "GREATEREQUAL" },
46  { ComparisonOperation::Less, "LESS" },
47  { ComparisonOperation::LessEqual, "LESSEQUAL" },
48 };
49 
50 int calculate_num_elems_processed_per_iteration(const ITensorInfo &input)
51 {
52  return 16 / input.element_size();
53 }
54 
55 Status validate_arguments(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output, ComparisonOperation operation)
56 {
58  ARM_COMPUTE_RETURN_ERROR_ON(input1.data_type() == DataType::UNKNOWN);
60  ARM_COMPUTE_RETURN_ERROR_ON(supported_comparison_ops.count(operation) == 0);
61 
62  const TensorShape out_shape = TensorShape::broadcast_shape(input1.tensor_shape(), input2.tensor_shape());
63  ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible");
64 
65  // Validate in case of configured output
66  if(output.total_size() > 0)
67  {
69  ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, output.tensor_shape(), 0),
70  "Wrong shape for output");
71  }
72 
73  return Status{};
74 }
75 
76 std::pair<Status, Window> validate_and_configure_window(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output)
77 {
78  const TensorShape &out_shape = TensorShape::broadcast_shape(input1.tensor_shape(), input2.tensor_shape());
79  const unsigned int num_elems_processed_per_iteration = calculate_num_elems_processed_per_iteration(input1);
80 
81  // Auto initialize output if not initialized
82  auto_init_if_empty(output, out_shape, 1, DataType::U8, QuantizationInfo());
83 
84  Window win = calculate_max_window(out_shape, Steps(num_elems_processed_per_iteration));
85  Window win_input1 = win.broadcast_if_dimension_le_one(input1);
86  Window win_input2 = win.broadcast_if_dimension_le_one(input2);
87 
88  AccessWindowHorizontal input1_access(&input1, 0, num_elems_processed_per_iteration);
89  AccessWindowHorizontal input2_access(&input2, 0, num_elems_processed_per_iteration);
90  AccessWindowHorizontal output_access(&output, 0, num_elems_processed_per_iteration);
91 
92  bool window_changed = update_window_and_padding(win_input1, input1_access)
93  || update_window_and_padding(win_input2, input2_access)
94  || update_window_and_padding(win, output_access);
95 
96  Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
97  return std::make_pair(err, win);
98 }
99 } // namespace
100 
102  : _input1(nullptr), _input2(nullptr), _output(nullptr)
103 {
105 }
106 
107 void CLComparisonKernel::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ComparisonOperation operation)
108 {
109  configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output, operation);
110 }
111 
112 void CLComparisonKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ComparisonOperation operation)
113 {
114  ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
115  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*input1->info(), *input2->info(), *output->info(), operation));
116 
117  // Configure kernel window
118  auto win_config = validate_and_configure_window(*input1->info(), *input2->info(), *output->info());
119  ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
120 
121  _input1 = input1;
122  _input2 = input2;
123  _output = output;
124 
125  const std::string &operation_name = supported_comparison_ops.at(operation);
126  std::string kernel_name = "compare_" + lower_string(operation_name);
127 
128  // Set kernel build options
129  std::set<std::string> build_opts;
130  build_opts.emplace("-DDATA_TYPE=" + get_cl_type_from_data_type(input1->info()->data_type()));
131  build_opts.emplace("-DVEC_SIZE=" + support::cpp11::to_string(calculate_num_elems_processed_per_iteration(*input1->info())));
132  build_opts.emplace("-DOP=" + operation_name);
133  build_opts.emplace("-DOP_NAME=" + lower_string(operation_name));
134  if(is_data_type_quantized(input1->info()->data_type()))
135  {
136  const UniformQuantizationInfo iq1_info = input1->info()->quantization_info().uniform();
137  const UniformQuantizationInfo iq2_info = input2->info()->quantization_info().uniform();
138 
139  build_opts.emplace("-DOFFSET_IN1=" + support::cpp11::to_string(iq1_info.offset));
140  build_opts.emplace("-DOFFSET_IN2=" + support::cpp11::to_string(iq2_info.offset));
141  build_opts.emplace("-DSCALE_IN1=" + float_to_string_with_full_precision(iq1_info.scale));
142  build_opts.emplace("-DSCALE_IN2=" + float_to_string_with_full_precision(iq2_info.scale));
143  kernel_name += "_quantized";
144  }
145 
146  // Create kernel
147  _kernel = create_kernel(compile_context, kernel_name, build_opts);
148 
149  ICLKernel::configure_internal(win_config.second);
150 
151  // Set config_id for enabling LWS tuning
152  _config_id = kernel_name;
153  _config_id += "_";
154  _config_id += lower_string(string_from_data_type(input1->info()->data_type()));
155  _config_id += "_";
156  _config_id += support::cpp11::to_string(output->info()->dimension(0));
157  _config_id += "_";
158  _config_id += support::cpp11::to_string(output->info()->dimension(1));
159  _config_id += lower_string(string_from_data_layout(input1->info()->data_layout()));
160 }
161 
162 Status CLComparisonKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ComparisonOperation operation)
163 {
164  ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output);
165 
166  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(*input1, *input2, *output, operation));
167  ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(*input1->clone(), *input2->clone(), *output->clone()).first);
168 
169  return Status{};
170 }
171 
172 void CLComparisonKernel::run(const Window &window, cl::CommandQueue &queue)
173 {
176 
177  const TensorShape &in_shape1 = _input1->info()->tensor_shape();
178  const TensorShape &in_shape2 = _input2->info()->tensor_shape();
179  const TensorShape &out_shape = _output->info()->tensor_shape();
180 
181  bool can_collapse = true;
182  const bool is_vector = in_shape1.num_dimensions() == 1 || in_shape2.num_dimensions() == 1;
183  if(std::min(in_shape1.total_size(), in_shape2.total_size()) > 1 && !is_vector)
184  {
185  can_collapse = (std::min(in_shape1.num_dimensions(), in_shape2.num_dimensions()) > Window::DimZ);
186  for(size_t d = Window::DimZ; can_collapse && (d < out_shape.num_dimensions()); d++)
187  {
188  can_collapse = (in_shape1[d] == in_shape2[d]);
189  }
190  }
191 
192  bool has_collapsed = false;
193  Window collapsed = can_collapse ? window.collapse_if_possible(ICLKernel::window(), Window::DimZ, &has_collapsed) : window;
194 
195  const TensorShape &in_shape1_collapsed = has_collapsed ? in_shape1.collapsed_from(Window::DimZ) : in_shape1;
196  const TensorShape &in_shape2_collapsed = has_collapsed ? in_shape2.collapsed_from(Window::DimZ) : in_shape2;
197 
198  Window slice = collapsed.first_slice_window_3D();
199  Window slice_input1 = slice.broadcast_if_dimension_le_one(in_shape1_collapsed);
200  Window slice_input2 = slice.broadcast_if_dimension_le_one(in_shape2_collapsed);
201 
202  do
203  {
204  unsigned int idx = 0;
205 
206  add_3D_tensor_argument(idx, _input1, slice_input1);
207  add_3D_tensor_argument(idx, _input2, slice_input2);
208  add_3D_tensor_argument(idx, _output, slice);
209 
210  enqueue(queue, *this, slice, lws_hint());
211 
212  ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input1));
213  ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input2));
214  }
215  while(collapsed.slide_window_slice_3D(slice));
216 }
217 
219 {
220  const int num_elems_processed_per_iteration = calculate_num_elems_processed_per_iteration(*_input1->info());
221 
222  const unsigned int replicateSize = _output->info()->dimension(0) - std::min(_input1->info()->dimension(0), _input2->info()->dimension(0));
223  const unsigned int border = std::min<unsigned int>(num_elems_processed_per_iteration - 1U, replicateSize);
224  return BorderSize{ 0, border, 0, 0 };
225 }
226 } // namespace arm_compute
bool is_data_type_quantized(DataType dt)
Check if a given data type is of quantized type.
Definition: Utils.h:981
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
#define ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(tensor)
Definition: CLValidate.h:35
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
Shape of a tensor.
Definition: TensorShape.h:39
virtual size_t dimension(size_t index) const =0
Return the size of the requested dimension.
Container for 2D border size.
Definition: Types.h:269
void enqueue(cl::CommandQueue &queue, ICLKernel &kernel, const Window &window, const cl::NDRange &lws_hint=CLKernelLibrary::get().default_ndrange(), bool use_dummy_work_items=false)
Add the kernel to the command queue with the given window.
Definition: ICLKernel.cpp:32
cl::NDRange lws_hint() const
Return the Local-Workgroup-Size hint.
Definition: ICLKernel.h:318
TensorShape collapsed_from(size_t start) const
Return a copy with collapsed dimensions starting from a given point.
Definition: TensorShape.h:161
1 channel, 1 U8 per channel
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:204
std::string to_string(T &&value)
Convert integer and float values to string.
virtual DataType data_type() const =0
Data type used for each element of the tensor.
static TensorShape broadcast_shape(const Shapes &... shapes)
If shapes are broadcast compatible, return the broadcasted shape.
Definition: TensorShape.h:211
void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ComparisonOperation operation)
Set the inputs and output tensors.
static CLKernelLibrary & get()
Access the KernelLibrary singleton.
Store the tensor&#39;s metadata.
Definition: ITensorInfo.h:40
#define ARM_COMPUTE_ERROR_THROW_ON(status)
Definition: Error.h:455
Quantization info when assuming per layer quantization.
Status class.
Definition: Error.h:52
std::string lower_string(const std::string &val)
Lower a given string.
Definition: Utils.cpp:326
#define ARM_COMPUTE_RETURN_ERROR_ON(cond)
If the condition is true, an error is returned.
Definition: Error.h:296
void add_3D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)
Add the passed 3D tensor&#39;s parameters to the object&#39;s kernel&#39;s arguments starting from the index idx...
Definition: ICLKernel.h:214
Copyright (c) 2017-2021 Arm Limited.
#define ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(...)
Definition: Validate.h:159
cl::Kernel create_kernel(const CLCompileContext &ctx, const std::string &kernel_name, const std::set< std::string > &build_opts=std::set< std::string >())
Creates an opencl kernel using a compile context.
Definition: CLHelpers.cpp:391
const std::string & string_from_data_type(DataType dt)
Convert a data type identity into a string.
Definition: Utils.cpp:135
bool update_window_and_padding(Window &win, Ts &&... patterns)
Update window and padding size for each of the access patterns.
Definition: WindowHelpers.h:46
#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
std::string float_to_string_with_full_precision(float val)
Create a string with the float in full precision.
Definition: Utils.h:1075
virtual const TensorShape & tensor_shape() const =0
Size for each dimension of the tensor.
CLComparisonKernel()
Default constructor.
size_t total_size() const
Collapses all dimensions to a single linear total size.
Definition: TensorShape.h:172
unsigned int num_elems_processed_per_iteration
UniformQuantizationInfo uniform() const
Return per layer quantization info.
std::string get_cl_type_from_data_type(const DataType &dt)
Translates a tensor data type to the appropriate OpenCL type.
Definition: CLHelpers.cpp: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.
bool have_different_dimensions(const Dimensions< T > &dim1, const Dimensions< T > &dim2, unsigned int upper_dim)
Definition: Validate.h:47
ComparisonOperation
Supported comparison operations.
Definition: Types.h:173
Window broadcast_if_dimension_le_one(const TensorShape &shape) const
Don&#39;t advance in the dimension where shape is less equal to 1.
Definition: Window.inl:120
void run(const Window &window, cl::CommandQueue &queue) override
Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue...
Elementeise CL kernel type.
Definition: CLTypes.h:84
bool slide_window_slice_3D(Window &slice) const
Slide the passed 3D window slice.
Definition: Window.h:335
virtual QuantizationInfo quantization_info() const =0
Get the quantization settings (scale and offset) of the tensor.
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:915
CLCompileContext class.
Interface for OpenCL tensor.
Definition: ICLTensor.h:42
const std::string & string_from_data_layout(DataLayout dl)
Convert a data layout identity into a string.
Definition: Utils.cpp:123
#define ARM_COMPUTE_CREATE_ERROR(error_code, msg)
Creates an error with a given message.
Definition: Error.h:159
static constexpr size_t DimZ
Alias for dimension 2 also known as Z dimension.
Definition: Window.h:47
unsigned int num_dimensions() const
Returns the effective dimensionality of the tensor.
Definition: Dimensions.h:143
#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(...)
Definition: Validate.h:541
#define ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)
Definition: Validate.h:788
static Status validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ComparisonOperation operation)
Static function to check if given info will lead to a valid configuration of CLComparisonKernel.
#define ARM_COMPUTE_RETURN_ERROR_ON_MSG(cond, msg)
If the condition is true, an error is returned.
Definition: Error.h:244
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:157
Window first_slice_window_3D() const
First 3D slice of the window.
Definition: Window.h:291
std::string kernel_name
BorderSize border_size() const override
The size of the border for that kernel.
Describe a multidimensional execution window.
Definition: Window.h:39
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:201
SimpleTensor< T > slice(const SimpleTensor< T > &src, Coordinates starts, Coordinates ends)
virtual DataLayout data_layout() const =0
Get the data layout of the tensor.