rsqr - Code Search

src/crypto/internal/nistec/p256_asm_amd64.s

	ST (r)

	CALL p256SqrInternal(SB)	// rsqr = rˆ2
	ST (rsqr)

	LDacc (h)
	CALL p256SqrInternal(SB)	// hsqr = hˆ2
	ST (hsqr)

	LDt (h)
	CALL p256MulInternal(SB)	// hcub = hˆ3
	ST (hcub)

	LDt (y1in)
	CALL p256MulInternal(SB)	// y1 * hˆ3
	ST (s2)

	LDacc (x1in)
	LDt (hsqr)
	CALL p256MulInternal(SB)	// u1 * hˆ2
	ST (h)

Registered: Wed Jun 12 16:32:35 UTC 2024

- Last Modified: Mon Mar 04 17:29:44 UTC 2024

- 39.8K bytes

- Viewed (0)

github.com/golang/go

src/crypto/internal/nistec/p256_asm_arm64.s

	STx(r)

	CALL	p256SqrInternal<>(SB)    // rsqr = rˆ2
	STy	(rsqr)

	LDx(h)
	CALL	p256SqrInternal<>(SB)    // hsqr = hˆ2
	STy(hsqr)

	CALL	p256MulInternal<>(SB)    // hcub = hˆ3
	STy(hcub)

	LDx(y1in)
	CALL	p256MulInternal<>(SB)    // y1 * hˆ3
	STy(s2)

	LDP	hsqr(0*8), (x0, x1)
	LDP	hsqr(2*8), (x2, x3)
	LDP	0*16(a_ptr), (y0, y1)
	LDP	1*16(a_ptr), (y2, y3)

Registered: Wed Jun 12 16:32:35 UTC 2024

- Last Modified: Mon Mar 04 17:29:44 UTC 2024

- 29.7K bytes

- Viewed (0)

github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/tests/prepare-tf.mlir

//              rsqrt(variance + epsilon)
// CHECK:  %[[RSQRT:.*]] = "tf.Rsqrt"(%[[ADD1]])
//              scale * rsqrt(variance + epsilon)
// CHECK:  %[[MUL1:.*]] = "tf.Mul"(%[[ARG1:.*]], %[[RSQRT]])
//              x * scale * rsqrt(variance + epsilon)
// CHECK:  %[[MUL2:.*]] = "tf.Mul"(%[[ARG0:.*]], %[[MUL1]])
//              mean * scale * rsqrt(variance + epsilon)

Registered: Sun Jun 16 05:45:23 UTC 2024

- Last Modified: Wed May 29 07:26:59 UTC 2024

- 59.8K bytes

- Viewed (0)

github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/stablehlo/tests/unfuse_mhlo_batch_norm.mlir

  // CHECK-DAG: %[[EPS_BCAST:.+]] = mhlo.constant dense<1.001000e-05> : tensor<256xf32>
  // CHECK-DAG: %[[VARIANCE_EPS:.+]] = mhlo.add %[[VARIANCE]], %[[EPS_BCAST]] : tensor<256xf32>
  // CHECK-DAG: %[[VARIANCE_EPS_RSQRT:.+]] = mhlo.rsqrt %[[VARIANCE_EPS]] : tensor<256xf32>
  // CHECK-DAG: %[[MULTIPLIER:.+]] = mhlo.multiply %[[VARIANCE_EPS_RSQRT]], %[[SCALE]] : tensor<256xf32>
  // CHECK-DAG: %[[MUL_MEAN:.+]] = mhlo.multiply %[[MULTIPLIER]], %[[MEAN]] : tensor<256xf32>

Registered: Sun Jun 16 05:45:23 UTC 2024

- Last Modified: Sat Apr 06 15:32:52 UTC 2024

- 10.4K bytes

- Viewed (0)

github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/transforms/prepare_patterns.td

    $t, $m, $v, $beta, $gamma, F32Attr:$variance_epsilon, ConstBoolAttrFalse:$scale_after_normalization),
  (TF_AddOp
    (TF_MulOp $t, (TF_RsqrtOp:$rsqrt (TF_AddOp $v, (TF_ConstOp $variance_epsilon)))),
    (TF_SubOp $beta, (TF_MulOp $m, $rsqrt)))>;
def ConvertBatchNormWithGlobalNormalization_2 : Pat<
  (TF_BatchNormWithGlobalNormalizationOp

Registered: Sun Jun 16 05:45:23 UTC 2024

- Last Modified: Tue Apr 30 00:40:15 UTC 2024

- 10.5K bytes

- Viewed (0)

github.com/golang/go

src/math/big/nat.go

				// to check performance before making changes.
				zz = zz.sqr(z)
				zz, z = z, zz
				z = z.trunc(z, logM)

				zz = zz.sqr(z)
				zz, z = z, zz
				z = z.trunc(z, logM)

				zz = zz.sqr(z)
				zz, z = z, zz
				z = z.trunc(z, logM)

				zz = zz.sqr(z)
				zz, z = z, zz
				z = z.trunc(z, logM)
			}

Registered: Wed Jun 12 16:32:35 UTC 2024

- Last Modified: Mon May 13 21:31:58 UTC 2024

- 31.7K bytes

- Viewed (0)

github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/vhlo.mlir

//CHECK-NEXT: return %0 : tensor<1x30x1xi32>
//CHECK-NEXT:}

func.func @rsqrt(%arg0: tensor<1x1x1x96xf32>) -> tensor<1x1x1x96xf32> {
 %0 = "vhlo.rsqrt_v1" (%arg0) : (tensor<1x1x1x96xf32>) -> tensor<1x1x1x96xf32>
 func.return %0 : tensor<1x1x1x96xf32>
}

//CHECK:func.func private @rsqrt(%arg0: tensor<1x1x1x96xf32>) -> tensor<1x1x1x96xf32> {

Registered: Sun Jun 16 05:45:23 UTC 2024

- Last Modified: Thu Mar 14 19:15:40 UTC 2024

- 31.9K bytes

- Viewed (1)

github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/tensorflow/transforms/lower_tf.td

        $round_val
      ),
      /*incompatible_shape_error*/ConstBoolAttrTrue
    ),
    $zero,
    $rounded
  )>;

//===----------------------------------------------------------------------===//
// Rsqrt op patterns.
//===----------------------------------------------------------------------===//

// RsqrtGrad(lhs, rhs) = (lhs * lhs * lhs) * (rhs / -2)
def LowerRsqrtGradOp : Pat<
  (TF_RsqrtGradOp $lhs, $rhs),

Registered: Sun Jun 16 05:45:23 UTC 2024

- Last Modified: Tue Jun 04 13:30:42 UTC 2024

- 24.7K bytes

- Viewed (0)

github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/tests/const-fold.mlir

  %8 = "tfl.sin"(%1) : (tensor<f32>) -> tensor<f32>
  %9 = "tfl.cos"(%2) : (tensor<f32>) -> tensor<f32>
  %10 = "tfl.log"(%3) : (tensor<f32>) -> tensor<f32>
  %11 = "tfl.sqrt"(%4) : (tensor<f32>) -> tensor<f32>
  %12 = "tfl.rsqrt"(%5) : (tensor<f32>) -> tensor<f32>
  %13 = "tfl.square"(%6) : (tensor<f32>) -> tensor<f32>

  func.return %7, %8, %9, %10, %11, %12, %13 : tensor<f32>, tensor<f32>, tensor<f32>, tensor<f32>, tensor<f32>, tensor<f32>, tensor<f32>

Registered: Sun Jun 16 05:45:23 UTC 2024

- Last Modified: Thu May 02 09:41:17 UTC 2024

- 45.8K bytes

- Viewed (0)

github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/transforms/optimize_patterns.td

// TODO(karimnosseir): Add constraints that the kernel code assumes.
// constraint on axis and depth.
multiclass L2NormalizePatterns<Op FirstOp, Op SecondOp> {
  // This pattern constructs L2NormalizationOp from
  // Mul->Rsqrt->Sum->Square Or
  // Div->sqrt->Sum->Square
  def L2NormalizePattern1#FirstOp#SecondOp : Pat<
                  (FirstOp $x,
                     (SecondOp
                        (TFL_SumOp

Registered: Sun Jun 16 05:45:23 UTC 2024

- Last Modified: Thu May 16 20:31:41 UTC 2024

- 66.4K bytes

- Viewed (0)

Search Options