#!/usr/bin/env bash
#
# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

    }

    /**
     * Auto-resize textarea based on content
     */
    function autoResizeTextarea() {
        var textarea = elements.chatInput[0];
        textarea.style.height = 'auto';
        textarea.style.height = Math.min(textarea.scrollHeight, 150) + 'px';
    }

    /**
     * Update character counter
     */
    function updateCharCount() {
        var count = elements.chatInput.val().length;

// Copyright 2012 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.

package p1

import (
	ptwo "p2"
)

const (
	ConstChase2 = constChase // forward declaration to unexported ident
	constChase  = AIsLowerA  // forward declaration to exported ident

	// Deprecated: use B.
	A         = 1
	a         = 11
	A64 int64 = 1

// Copyright 2012 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.

//go:build unix

package tar

import (
	"io/fs"
	"os/user"
	"runtime"
	"strconv"
	"sync"
	"syscall"
)

func init() {
	sysStat = statUnix
}

// userMap and groupMap cache UID and GID lookups for performance reasons.

	gf2MatrixSquare(even, odd)

	// put operator for four zero bits in odd
	gf2MatrixSquare(odd, even)

	// apply len2 zeros to crc1 (first square will put the operator for one
	// zero byte, eight zero bits, in even)
	crc1n := uint64(crc1)
	for {
		// apply zeros operator for this bit of len2
		gf2MatrixSquare(even, odd)
		if len2&1 != 0 {
			crc1n = gf2MatrixTimes(even, crc1n)
		}
		len2 >>= 1

        `tf.keras.mixed_precision.experimental.LossScaleOptimizer`, the weights
        of the `DynanmicLossScale` are copied into the `LossScaleOptimizer`
        instead of being reused. This means modifying the weights of the
        `DynamicLossScale` will no longer affect the weights of the
        LossScaleOptimizer, and vice versa.

Esto significa que, aunque tus clientes de API solo pueden enviar strings como claves, mientras esos strings contengan enteros puros, Pydantic los convertirá y validará.

Y el `dict` que recibas como `weights` tendrá realmente claves `int` y valores `float`.

///

## Resumen { #recap }

Con **FastAPI** tienes la máxima flexibilidad proporcionada por los modelos Pydantic, manteniendo tu código simple, corto y elegante.

// Copyright 2012 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.

// Addr2line is a minimal simulation of the GNU addr2line tool,
// just enough to support pprof.
//
// Usage:
//
//	go tool addr2line binary
//
// Addr2line reads hexadecimal addresses, one per line and with optional 0x prefix,

/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,

/* Copyright 2015 The TensorFlow Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,