Searched defs:gradient (Results 1 - 25 of 33) sorted by relevance

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/external/apache-commons-math/src/main/java/org/apache/commons/math/analysis/
H A DDifferentiableMultivariateRealFunction.java33 * needed, it may be more efficient to use the {@link #gradient()} method which will
43 * Returns the gradient function.
47 * @return the gradient function
49 MultivariateVectorialFunction gradient(); method in interface:DifferentiableMultivariateRealFunction
/external/ImageMagick/Magick++/demo/
H A Ddemo.cpp229 cout << " gradient ..." << endl;
230 Image gradient; local
231 gradient.size( "130x194" );
232 gradient.read( "gradient:#20a0ff-#ffff00" );
233 gradient.label( "Gradient" );
234 images.push_back( gradient );
/external/apache-commons-math/src/main/java/org/apache/commons/math/optimization/fitting/
H A DParametricGaussianFunction.java94 * Computes the gradient vector for a four variable version of the function
97 * computing the gradient vector for the function <tt>f(x)</tt> (which would
99 * it's a one-dimensional function), computes the gradient vector for the
103 * The components of the computed gradient vector are the partial
114 * <tt>d</tt> for computation of gradient vector of <tt>f(a, b, c,
117 * @return gradient vector of <tt>f(a, b, c, d)</tt>
124 public double[] gradient(double x, double[] parameters) throws ZeroException { method in class:ParametricGaussianFunction
142 * the <code>value</code> and <code>gradient</code> methods.
H A DParametricRealFunction.java41 * Compute the gradient of the function with respect to its parameters.
47 double[] gradient(double x, double[] parameters) method in interface:ParametricRealFunction
H A DHarmonicFitter.java121 public double[] gradient(double x, double[] parameters) { method in class:HarmonicFitter.ParametricHarmonicFunction
H A DPolynomialFitter.java87 public double[] gradient(double x, double[] parameters) { method in class:PolynomialFitter.ParametricPolynomial
88 final double[] gradient = new double[parameters.length];
91 gradient[i] = xn;
94 return gradient;
/external/apache-commons-math/src/main/java/org/apache/commons/math/optimization/general/
H A DAbstractScalarDifferentiableOptimizer.java72 /** Number of gradient evaluations. */
78 /** Objective function gradient. */
79 private MultivariateVectorialFunction gradient; field in class:AbstractScalarDifferentiableOptimizer
148 * Compute the gradient vector.
149 * @param evaluationPoint point at which the gradient must be evaluated
150 * @return gradient at the specified point
151 * @exception FunctionEvaluationException if the function gradient
156 return gradient.value(evaluationPoint);
189 gradient = f.gradient();
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/external/swiftshader/src/Renderer/
H A DColor.hpp52 static Color<T> gradient(const Color<T> &c1, const Color<T> &c2, float d);
448 inline Color<T> Color<T>::gradient(const Color<T> &c1, const Color<T> &c2, float d) function in class:sw::Color
H A DSetupProcessor.hpp73 Gradient gradient[MAX_FRAGMENT_INPUTS][4]; member in union:sw::SetupProcessor::States::__anon22367
/external/tensorflow/tensorflow/compiler/tf2xla/kernels/
H A Dwhile_op.cc66 for (const auto& gradient : resource->tensor_array_gradients()) {
67 arg.tensor_array_gradients.insert(gradient.first);
129 // gradient TensorArrays will be created by the TensorArrayGradV3 operator.
134 // 1) once with uninitialized resource inputs and no TensorArray gradient
168 VLOG(4) << "TensorArray " << resource->name() << " accessed gradient "
170 XlaResource* gradient; local
172 grad_source, builder, &gradient));
177 for (const auto& gradient : resource->tensor_array_gradients()) {
178 arg.tensor_array_gradients.insert(gradient.first);
H A Dfake_quantize_ops.cc162 xla::ComputationDataHandle gradient = ctx->Input(0); variable
178 b->Select(between_nudged_min_max, gradient, zeroes);
246 xla::ComputationDataHandle gradient = ctx->Input(0); variable
264 b->Select(between_nudged_min_max, gradient, zeroes);
269 b->ReduceAll(b->Select(below_min, gradient, zeroes), zero,
275 b->ReduceAll(b->Select(above_max, gradient, zeroes), zero,
H A Dtensor_array_ops.cc582 // Finds or looks up the corresponding gradient TensorArray, which stores
584 XlaResource* gradient; variable
586 ctx, resource->GetOrCreateTensorArrayGradient(source_, b, &gradient));
588 ctx->SetResourceOutput(0, gradient);
/external/tensorflow/tensorflow/compiler/tf2xla/
H A Dxla_resource.cc43 for (const string& gradient : tensor_array_gradients) {
44 tensor_array_gradients_[gradient].reset(
128 << " gradient: " << source;
130 std::unique_ptr<XlaResource>& gradient = tensor_array_gradients_[source]; local
131 if (!gradient) {
137 gradient.reset(
143 *gradient_out = gradient.get();
155 for (const auto& gradient : tensor_array_gradients_) {
156 elems.push_back(gradient.second->value_);
181 XlaResource* gradient; local
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/external/tensorflow/tensorflow/core/kernels/
H A Dctc_loss_op.cc140 Tensor* gradient; variable
142 ctx->allocate_output("gradient", inputs_shape, &gradient));
143 auto gradient_t = gradient->tensor<float, 3>();
H A Dfake_quant_ops.cc118 void Operate(OpKernelContext* context, const Tensor& gradient, argument
120 OperateNoTemplate(context, gradient, input, output);
123 void OperateNoTemplate(OpKernelContext* context, const Tensor& gradient, argument
125 OP_REQUIRES(context, input.IsSameSize(gradient),
126 InvalidArgument("gradient and input must be the same size"));
128 functor(context->eigen_device<Device>(), gradient.flat<float>(),
230 const Tensor& gradient = context->input(0); variable
232 OP_REQUIRES(context, input.IsSameSize(gradient),
233 InvalidArgument("gradient and input must be the same size"));
251 functor(context->eigen_device<Device>(), gradient
367 const Tensor& gradient = context->input(0); variable
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H A Dpooling_ops_3d_sycl.h400 // maximum value in the input tensor. This is then the index of the gradient to
627 // input value at this index. Then for each gradient in this window, compute
629 // this size to scale the gradient accordingly. Add this scaled gradient to the
679 T gradient = T(0); local
704 gradient += input_backprop_n[idx] / static_cast<T>(window_size);
708 output_backprop[index] = gradient;
/external/ImageMagick/MagickCore/
H A Dpaint.c400 % o type: the gradient type: linear or radial.
402 % o spread: the gradient spread meathod: pad, reflect, or repeat.
422 *gradient;
428 Set gradient start-stop end points.
437 gradient=(&draw_info->gradient);
438 gradient->type=type;
439 gradient->bounding_box.width=image->columns;
440 gradient->bounding_box.height=image->rows;
441 artifact=GetImageArtifact(image,"gradient
419 *gradient; local
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H A Ddraw.h190 gradient; member in struct:_ElementReference
226 gradient; member in struct:_DrawInfo
H A Ddraw.c329 clone_info->gradient=draw_info->gradient;
330 if (draw_info->gradient.stops != (StopInfo *) NULL)
335 number_stops=clone_info->gradient.number_stops;
336 clone_info->gradient.stops=(StopInfo *) AcquireQuantumMemory((size_t)
337 number_stops,sizeof(*clone_info->gradient.stops));
338 if (clone_info->gradient.stops == (StopInfo *) NULL)
341 (void) CopyMagickMemory(clone_info->gradient.stops,
342 draw_info->gradient.stops,(size_t) number_stops*
343 sizeof(*clone_info->gradient
3303 GetStopColorOffset(const GradientInfo *gradient, const ssize_t x,const ssize_t y) argument
3381 *gradient; local
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/external/opencv/cv/src/
H A Dcvsnakes.cpp66 // if _CV_SNAKE_GRAD - magnitude of gradient is energy
100 float *gradient = NULL; local
149 gradient = (float *) cvAlloc( roi.height * roi.width * sizeof( float ));
151 if( !gradient )
156 cvFree( &gradient );
159 /* clear map - no gradient computed */
315 gradient[(y*WTILE_SIZE + l) * roi.width + x*WTILE_SIZE + m] =
325 gradient[(pt[i].y + j) * roi.width + pt[i].x + k];
401 cvFree( &gradient );
/external/tensorflow/tensorflow/python/eager/
H A Dbackprop.py94 """Pretends to be a tf.Operation for the gradient functions."""
112 """Calls the gradient function of the op.
141 # gradient function registration site, to be less error-prone
247 # gradient functions.
248 # Some gradient functions can accept None arguments for gradients. The following
249 # maps the operation name to the indices at which the corresponding gradient
251 # e.g. FusedBatchNorm outputs 5 values and hence receives 5 gradient values
252 # during backprop. However the gradient function uses only the first of those
254 # indicates that only the gradient corresponding to index 0 is used, and the
255 # gradient value
889 def gradient(self, target, sources, output_gradients=None): member in class:GradientTape
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/external/tensorflow/tensorflow/core/framework/
H A Dfunction.h309 // Adds gradient definition 'grad' to this function library.
320 // Remove gradient of function `func` from the library. Returns non-OK Status
321 // unless `func` has a gradient.
334 // If the gradient function for 'func' is specified explicitly in
335 // the library, returns the gradient function name. Otherwise,
599 // To register a gradient function for a builtin op, one should use
603 // converted into ::tensorflow::gradient::Creator, which is
606 // A ::tensorflow::gradient::Creator should populate in FunctionDef* with a
607 // definition of a brain function which compute the gradient for the
638 // gradient functio
657 namespace gradient { namespace in namespace:tensorflow
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H A Dfunction.cc115 // Right now the C++ function gradient code assumes it can pass
116 // all the attrs of the function to the gradient, and any attrs that
117 // the gradient doesn't care about will be ignored.
931 for (const auto& grad : def_lib.gradient()) {
990 "Cannot assign gradient function '", grad.gradient_func(), "' to '",
991 grad.function_name(), "' because it already has gradient function ",
1054 for (const GradientDef& grad : lib_def.gradient()) {
1080 return errors::InvalidArgument("Tried to remove non-existent gradient ",
1122 // If ndef is SymbolicGradient[f=Foo], we use Foo's gradient or
1130 // If 'func' has a user-defined gradient functio
1318 namespace gradient { namespace in namespace:tensorflow
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/external/skia/tests/
H A DImageFilterTest.cpp588 SkBitmap gradient = make_gradient_circle(width, height); local
590 gradient));
/external/skqp/tests/
H A DImageFilterTest.cpp588 SkBitmap gradient = make_gradient_circle(width, height); local
590 gradient));

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