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value_and_grad_f = jax.value_and_grad(train_apply_f, has_aux=False, allow_int=True)
grad_init = jax.tree_map(lambda x: jnp.zeros_like(x).astype(jnp.bfloat16), params_bf16)

def scan(f, init, xs):
    carry = init
    ys = []
    for i in range(xs[0].shape[0]):
        carry, y = f(carry, (xs[0][i], xs[1][i]))
        ys.append(y)
    return carry, jnp.stack(ys)

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def tree_flatten_with_names(pytree, is_leaf, path="", to_id=id):
    id_to_name = {}
    if getattr(pytree, "items", None):
        for k, v in pytree.items():
            k_path = f"{path}/{k}"
            if is_leaf(v):
                id_to_name[to_id(v)] = k_path
            else:
                id_to_name = {
                    **id_to_name,

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'''
python3.8 -m venv .venv
source .venv/bin/activate
pip install --upgrade pip setuptools
pip install -r requirements.txt
pip install --upgrade jax==0.2.12 jaxlib==0.1.67+cuda110 -f https://storage.googleapis.com/jax-releases/jax_releases.html
'''

import os
# xla

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def apply_reshard(pytree_params_in, pytree_params_out, shards_in, shards_out):

    def override_dtype(x):
        if x.dtype == np.dtype('V2'):
            x.dtype = jnp.bfloat16
        return x

    def is_leaf(x):
        return type(x) == np.ndarray

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import os
import io
import tempfile
import tensorflow as tf
import transformers

def write_to_file(writer, data):
    feature = { 'text': tf.train.Feature(int64_list=tf.train.Int64List(value=data)) }
    tf_example = tf.train.Example(features=tf.train.Features(feature=feature))
    writer.write(tf_example.SerializeToString())

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import sys
import os
import gzip
import json
import io
import argparse
import concurrent.futures

from tokenizers import Tokenizer

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import argparse

import numpy as np

import tensorflow as tf

class TFRecordResumableLoader:
    def __init__(self, files, batch_size, batch_prefetch, parse_fn, map_fn=lambda x: x):
        self.files = files
        self.batch_size = batch_size

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vim /usr/local/texlive/2016/texmf.cnf

max_print_line=2000
error_line=254
half_error_line=238


#!/bin/bash

for image_file in $(find Part_1/Chpt_9_Generator_and_Descriptor/figures -type f)

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{"input": [{"bbox": [206, 642, 206, 654], "text": "necessary", "id": 49}, {"bbox": [641, 175, 641, 185], "text": "AP", "id": 9}, {"bbox": [194, 554, 194, 564], "text": "suggest", "id": 37}, {"bbox": [10, 396, 10, 410], "text": "Drug", "id": 22}, {"bbox": [606, 106, 606, 117], "text": "Matthew", "id": 2}, {"bbox": [246, 551, 246, 562], "text": "factor.", "id": 38}, {"bbox": [73, 343, 73, 356], "text": "Arthurfort,", "id": 19}, {"bbox": [31, 275, 31, 286], "text": "Walter", "id": 11}, {"bbox": [29, 551, 29, 562], "text": "93.77", "id": 35}, {"bbox": [638, 141, 638, 151], "text": "4831", "id": 5}, {"bbox": [153, 507, 153, 518], "text": "Character", "id": 29}, {"bbox": [338, 639, 338, 651], "text": "break.", "id": 51}, {"bbox": [278, 595, 278, 607], "text": "staff.", "id": 43}, {"bbox": [106, 309, 106, 320], "text": "Knolls", "id": 15}, {"bbox": [46, 395, 46, 406], "text": "health", "id": 23}, {"bbox": [30, 639, 31, 652], "text": "720.8", "id": 46}, {"bbox": [617, 639, 617, 650], "text": "9685", "id": 47}, {"bbox

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{"input": [{"x": 71, "y": 10, "width": 5, "id": 191}, {"x": 6, "y": 0, "width": 5, "id": 127}, {"x": 38, "y": 12, "width": 4, "id": 145}, {"x": 51, "y": 2, "width": 3, "id": 152}, {"x": 20, "y": 4, "width": 2, "id": 6}, {"x": 10, "y": 12, "width": 4, "id": 90}, {"x": 19, "y": 8, "width": 4, "id": 222}, {"x": 0, "y": 10, "width": 5, "id": 107}, {"x": 20, "y": 12, "width": 3, "id": 20}, {"x": 45, "y": 8, "width": 4, "id": 29}, {"x": 15, "y": 12, "width": 2, "id": 86}, {"x": 56, "y": 10, "width": 4, "id": 252}, {"x": 61, "y": 4, "width": 3, "id": 174}, {"x": 25, "y": 2, "width": 3, "id": 69}, {"x": 35, "y": 8, "width": 3, "id": 193}, {"x": 12, "y": 0, "width": 2, "id": 221}, {"x": 18, "y": 0, "width": 2, "id": 239}, {"x": 38, "y": 10, "width": 2, "id": 172}, {"x": 6, "y": 10, "width": 4, "id": 189}, {"x": 46, "y": 12, "width": 5, "id": 183}, {"x": 11, "y": 8, "width": 3, "id": 196}, {"x": 15, "y": 8, "width": 3, "id": 134}, {"x": 57, "y": 2, "width": 2, "id": 45}, {"x": 35, "y": 10, "width": 2, "id": 223}, {"x":