namex==0.0.8 \
    --hash=sha256:32a50f6c565c0bb10aa76298c959507abdc0e850efe085dc38f3440fcb3aa90b \
    --hash=sha256:7ddb6c2bb0e753a311b7590f84f6da659dd0c05e65cb89d519d54c0a250c0487
    # via keras-nightly
numpy==1.23.5 ; python_version <= "3.11" \
    --hash=sha256:01dd17cbb340bf0fc23981e52e1d18a9d4050792e8fb8363cecbf066a84b827d \
    --hash=sha256:06005a2ef6014e9956c09ba07654f9837d9e26696a0470e42beedadb78c11b07 \

namex==0.0.8 \
    --hash=sha256:32a50f6c565c0bb10aa76298c959507abdc0e850efe085dc38f3440fcb3aa90b \
    --hash=sha256:7ddb6c2bb0e753a311b7590f84f6da659dd0c05e65cb89d519d54c0a250c0487
    # via keras-nightly
numpy==1.23.5 ; python_version <= "3.11" \
    --hash=sha256:01dd17cbb340bf0fc23981e52e1d18a9d4050792e8fb8363cecbf066a84b827d \
    --hash=sha256:06005a2ef6014e9956c09ba07654f9837d9e26696a0470e42beedadb78c11b07 \

00000160  c8 35 fe c2 9a 17 33 18  51 c2 cd 19 7c dc 5d c5  |.5....3.Q...|.].|
00000170  7c e6 d0 38 ab 28 0b 8c  78 51 aa 7f ef f0 9a c3  ||..8.(..xQ......|
00000180  df 26 d2 bc 1b b6 98 b1  16 35 9d f0 73 b7 15 f7  |.&.......5..s...|
00000190  7d 9f 3e fe 4c 75 e7 c7  5d cb c2 e5 29 4a 30 32  |}.>.Lu..]...)J02|
000001a0  e2 da 3c 2c 16 ba 89 41  28 5c 33 75 b3 ed d1 e6  |..<,...A(\3u....|

	a[129] = 0
	a[130] = 0
	a[131] = 0
	a[132] = 0
	a[133] = 0
	a[134] = 0
	a[135] = 0
	a[136] = 0
	a[137] = 0
	a[138] = 0
	a[139] = 0
	a[140] = 0
	a[141] = 0
	a[142] = 0
	a[143] = 0
	a[144] = 0
	a[145] = 0
	a[146] = 0
	a[147] = 0
	a[148] = 0
	a[149] = 0
	a[150] = 0
	a[151] = 0
	a[152] = 0
	a[153] = 0
	a[154] = 0
	a[155] = 0
	a[156] = 0
	a[157] = 0

  "durations" : [ {
    "testProject" : "bigNative",
    "linux" : 499
  }, {
    "testProject" : "mediumNative",
    "linux" : 178
  }, {
    "testProject" : "multiNative",
    "linux" : 1135
  }, {
    "testProject" : "smallNative",
    "linux" : 131
  } ]
}, {
  "scenario" : "org.gradle.performance.experiment.nativeplatform.NativePreCompiledHeaderPerformanceTest.clean assemble with precompiled headers",

=== "Python 3.9+"

    ```Python hl_lines="15-16"
    {!> ../../../docs_src/dependencies/tutorial008c_an_py39.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="14-15"
    {!> ../../../docs_src/dependencies/tutorial008c_an.py!}
    ```

=== "Python 3.8+ non-Annotated"

    !!! tip
        Prefer to use the `Annotated` version if possible.

  // more consecutive numbers are compressed and represented by the first and
  // last element of the series, separated by a hyphen.
  // For example, if the completed indexes are 1, 3, 4, 5 and 7, they are
  // represented as "1,3-5,7".
  // +optional
  optional string completedIndexes = 7;

  // uncountedTerminatedPods holds the UIDs of Pods that have terminated but

	ENOTDIR            = Errno(135)
	ENOTEMPTY          = Errno(136)
	ENOTTY             = Errno(137)
	ENXIO              = Errno(138)
	EPERM              = Errno(139)
	EPIPE              = Errno(140)
	EROFS              = Errno(141)
	ESPIPE             = Errno(142)
	ESRCH              = Errno(143)
	EXDEV              = Errno(144)
	E2BIG              = Errno(145)
	ELOOP              = Errno(146)

// Copyright 2009 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

// DNS client: see RFC 1035.
// Has to be linked into package net for Dial.

// TODO(rsc):
//	Could potentially handle many outstanding lookups faster.
//	Random UDP source port (net.Dial should do that for us).
//	Random request IDs.

package net

import (
	"context"
	"errors"

    %14 = stablehlo.subtract %9, %13 : tensor<1x3x3x4xf32>
    %15 = stablehlo.broadcast_in_dim %4, dims = [0, 1, 2, 3] : (tensor<1x1x1x4xf32>) -> tensor<1x3x3x4xf32>
    %16 = stablehlo.multiply %14, %15 : tensor<1x3x3x4xf32>
    %17 = call @uniform_quantize_1(%16, %5, %6) : (tensor<1x3x3x4xf32>, tensor<1x1x1x1xf32>, tensor<1x1x1x1xi8>) -> tensor<1x3x3x4xi8>