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Results 11 - 20 of 80 for AStride (0.2 sec)
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src/image/image.go
type RGBA struct { // Pix holds the image's pixels, in R, G, B, A order. The pixel at // (x, y) starts at Pix[(y-Rect.Min.Y)*Stride + (x-Rect.Min.X)*4]. Pix []uint8 // Stride is the Pix stride (in bytes) between vertically adjacent pixels. Stride int // Rect is the image's bounds. Rect Rectangle } func (p *RGBA) ColorModel() color.Model { return color.RGBAModel }
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Thu Oct 19 12:02:45 UTC 2023 - 34.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/composite_avg_pool_patterns.td
/*padding*/(GetAvgPoolOpPadAttr $old_val), /*stride_h*/(GetI32At<0> (GetAsVectorAttr<"stride"> $attrs)), /*stride_w*/(GetI32At<1> (GetAsVectorAttr<"stride"> $attrs)), /*fused_activation_function*/TFL_AF_None, (returnType (GetNhwcReturnTypeFromNchw $old_val))),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 23:16:05 UTC 2024 - 7.8K bytes - Viewed (0) -
src/unicode/letter.go
} if r <= range_.Hi { return range_.Stride == 1 || (r-range_.Lo)%range_.Stride == 0 } } return false } // binary search over ranges lo := 0 hi := len(ranges) for lo < hi { m := int(uint(lo+hi) >> 1) range_ := &ranges[m] if range_.Lo <= r && r <= range_.Hi { return range_.Stride == 1 || (r-range_.Lo)%range_.Stride == 0 } if r < range_.Lo { hi = m
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Mon Nov 06 20:02:46 UTC 2023 - 10K bytes - Viewed (0) -
src/image/draw/draw.go
ddelta = dst.Stride sdelta = src.Stride i0, i1, idelta = 0, dx*4, +4 } else { // If the source start point is higher than the destination start point, or equal height but to the left, // then we compose the rows in right-to-left, bottom-up order instead of left-to-right, top-down. d0 += (dy - 1) * dst.Stride s0 += (dy - 1) * src.Stride ddelta = -dst.Stride sdelta = -src.Stride
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Mon Mar 11 17:08:05 UTC 2024 - 33.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/bridge/optimize.mlir
// CHECK-DAG: %[[result:.*]] = chlo.broadcast_add %[[conv]], %[[combined]] // CHECK: return %[[result]] %0 = mhlo.convolution(%lhs, %rhs) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], lhs_dilate = [1, 1], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<?x3x2x1xi8>, tensor<2x1x1x1xi8>) -> tensor<?x2x2x1xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Feb 24 02:26:47 UTC 2024 - 10.7K bytes - Viewed (0) -
src/image/png/reader.go
srcPix = src.(*image.Gray).Pix dstPix, stride, rect = target.Pix, target.Stride, target.Rect bytesPerPixel = 1 case *image.Gray16: srcPix = src.(*image.Gray16).Pix dstPix, stride, rect = target.Pix, target.Stride, target.Rect bytesPerPixel = 2 case *image.NRGBA: srcPix = src.(*image.NRGBA).Pix dstPix, stride, rect = target.Pix, target.Stride, target.Rect bytesPerPixel = 4 case *image.NRGBA64:
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Thu Oct 19 12:02:45 UTC 2023 - 26K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/fuse_mhlo_convolution.mlir
// CHECK-DAG: %[[RESULT:.+]] = mhlo.convolution(%[[INPUT]], %[[NEW_FILTER]]) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = {{\[\[}}0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x256x256x3xf32>, tensor<1x1x3x2xf32>) -> tensor<1x256x256x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 4.4K bytes - Viewed (0) -
src/encoding/hex/hex_test.go
} } } func TestDumper(t *testing.T) { var in [40]byte for i := range in { in[i] = byte(i + 30) } for stride := 1; stride < len(in); stride++ { var out bytes.Buffer dumper := Dumper(&out) done := 0 for done < len(in) { todo := done + stride if todo > len(in) { todo = len(in) } dumper.Write(in[done:todo]) done = todo } dumper.Close()
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Wed May 08 19:30:23 UTC 2024 - 7.9K bytes - Viewed (0) -
test/fixedbugs/issue25776.go
type blas64_Triangular struct { Stride int Uplo int } // TriDense represents an upper or lower triangular matrix in dense storage // format. type TriDense struct { mat blas64_Triangular } func NewTriDense() *TriDense { return &TriDense{ mat: blas64_Triangular{ Stride: 3, Uplo: blas_Upper, }, } } func (t *TriDense) isUpper() bool {
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Thu Jun 14 20:08:10 UTC 2018 - 2.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/utils/tf_to_xla_attribute_utils.cc
Value stride_value = CreateScalarConstValue<int32_t>(builder, loc, stride); Value dilation_rate_value = CreateScalarConstValue<int32_t>(builder, loc, dilation_rate); Value effective_filter_size_op = scalar_add( scalar_mul(dilation_rate_value, scalar_sub(filter_size, one)), one); // output_size = (input_size + stride - 1) / stride Value output_size = scalar_div(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 17:58:54 UTC 2024 - 13.3K bytes - Viewed (0)