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https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git
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17c31aded9
The kernel tree builds some "composite" DTBs, where the final DTB is the result of applying one or more DTB overlays on top of a base DTB with fdtoverlay. The FIT image specification already supports configurations having one base DTB and overlays applied on top. It is then up to the bootloader to apply said overlays and either use or pass on the final result. This allows the FIT image builder to reuse the same FDT images for multiple configurations, if such cases exist. The decomposition function depends on the kernel build system, reading back the .cmd files for the to-be-packaged DTB files to check for the fdtoverlay command being called. This will not work outside the kernel tree. The function is off by default to keep compatibility with possible existing users. To facilitate the decomposition and keep the code clean, the model and compatitble string extraction have been moved out of the output_dtb function. The FDT image description is replaced with the base file name of the included image. Signed-off-by: Chen-Yu Tsai <wenst@chromium.org> Reviewed-by: Simon Glass <sjg@chromium.org> Signed-off-by: Masahiro Yamada <masahiroy@kernel.org>
332 lines
10 KiB
Python
Executable File
332 lines
10 KiB
Python
Executable File
#!/usr/bin/env python3
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# SPDX-License-Identifier: GPL-2.0+
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#
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# Copyright 2024 Google LLC
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# Written by Simon Glass <sjg@chromium.org>
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#
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"""Build a FIT containing a lot of devicetree files
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Usage:
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make_fit.py -A arm64 -n 'Linux-6.6' -O linux
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-o arch/arm64/boot/image.fit -k /tmp/kern/arch/arm64/boot/image.itk
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@arch/arm64/boot/dts/dtbs-list -E -c gzip
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Creates a FIT containing the supplied kernel and a set of devicetree files,
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either specified individually or listed in a file (with an '@' prefix).
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Use -E to generate an external FIT (where the data is placed after the
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FIT data structure). This allows parsing of the data without loading
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the entire FIT.
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Use -c to compress the data, using bzip2, gzip, lz4, lzma, lzo and
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zstd algorithms.
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Use -D to decompose "composite" DTBs into their base components and
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deduplicate the resulting base DTBs and DTB overlays. This requires the
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DTBs to be sourced from the kernel build directory, as the implementation
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looks at the .cmd files produced by the kernel build.
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The resulting FIT can be booted by bootloaders which support FIT, such
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as U-Boot, Linuxboot, Tianocore, etc.
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Note that this tool does not yet support adding a ramdisk / initrd.
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"""
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import argparse
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import collections
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import os
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import subprocess
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import sys
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import tempfile
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import time
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import libfdt
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# Tool extension and the name of the command-line tools
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CompTool = collections.namedtuple('CompTool', 'ext,tools')
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COMP_TOOLS = {
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'bzip2': CompTool('.bz2', 'bzip2'),
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'gzip': CompTool('.gz', 'pigz,gzip'),
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'lz4': CompTool('.lz4', 'lz4'),
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'lzma': CompTool('.lzma', 'lzma'),
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'lzo': CompTool('.lzo', 'lzop'),
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'zstd': CompTool('.zstd', 'zstd'),
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}
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def parse_args():
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"""Parse the program ArgumentParser
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Returns:
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Namespace object containing the arguments
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"""
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epilog = 'Build a FIT from a directory tree containing .dtb files'
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parser = argparse.ArgumentParser(epilog=epilog, fromfile_prefix_chars='@')
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parser.add_argument('-A', '--arch', type=str, required=True,
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help='Specifies the architecture')
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parser.add_argument('-c', '--compress', type=str, default='none',
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help='Specifies the compression')
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parser.add_argument('-D', '--decompose-dtbs', action='store_true',
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help='Decompose composite DTBs into base DTB and overlays')
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parser.add_argument('-E', '--external', action='store_true',
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help='Convert the FIT to use external data')
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parser.add_argument('-n', '--name', type=str, required=True,
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help='Specifies the name')
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parser.add_argument('-o', '--output', type=str, required=True,
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help='Specifies the output file (.fit)')
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parser.add_argument('-O', '--os', type=str, required=True,
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help='Specifies the operating system')
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parser.add_argument('-k', '--kernel', type=str, required=True,
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help='Specifies the (uncompressed) kernel input file (.itk)')
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parser.add_argument('-v', '--verbose', action='store_true',
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help='Enable verbose output')
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parser.add_argument('dtbs', type=str, nargs='*',
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help='Specifies the devicetree files to process')
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return parser.parse_args()
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def setup_fit(fsw, name):
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"""Make a start on writing the FIT
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Outputs the root properties and the 'images' node
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Args:
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fsw (libfdt.FdtSw): Object to use for writing
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name (str): Name of kernel image
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"""
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fsw.INC_SIZE = 65536
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fsw.finish_reservemap()
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fsw.begin_node('')
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fsw.property_string('description', f'{name} with devicetree set')
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fsw.property_u32('#address-cells', 1)
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fsw.property_u32('timestamp', int(time.time()))
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fsw.begin_node('images')
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def write_kernel(fsw, data, args):
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"""Write out the kernel image
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Writes a kernel node along with the required properties
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Args:
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fsw (libfdt.FdtSw): Object to use for writing
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data (bytes): Data to write (possibly compressed)
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args (Namespace): Contains necessary strings:
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arch: FIT architecture, e.g. 'arm64'
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fit_os: Operating Systems, e.g. 'linux'
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name: Name of OS, e.g. 'Linux-6.6.0-rc7'
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compress: Compression algorithm to use, e.g. 'gzip'
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"""
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with fsw.add_node('kernel'):
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fsw.property_string('description', args.name)
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fsw.property_string('type', 'kernel_noload')
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fsw.property_string('arch', args.arch)
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fsw.property_string('os', args.os)
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fsw.property_string('compression', args.compress)
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fsw.property('data', data)
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fsw.property_u32('load', 0)
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fsw.property_u32('entry', 0)
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def finish_fit(fsw, entries):
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"""Finish the FIT ready for use
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Writes the /configurations node and subnodes
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Args:
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fsw (libfdt.FdtSw): Object to use for writing
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entries (list of tuple): List of configurations:
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str: Description of model
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str: Compatible stringlist
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"""
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fsw.end_node()
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seq = 0
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with fsw.add_node('configurations'):
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for model, compat, files in entries:
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seq += 1
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with fsw.add_node(f'conf-{seq}'):
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fsw.property('compatible', bytes(compat))
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fsw.property_string('description', model)
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fsw.property('fdt', bytes(''.join(f'fdt-{x}\x00' for x in files), "ascii"))
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fsw.property_string('kernel', 'kernel')
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fsw.end_node()
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def compress_data(inf, compress):
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"""Compress data using a selected algorithm
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Args:
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inf (IOBase): Filename containing the data to compress
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compress (str): Compression algorithm, e.g. 'gzip'
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Return:
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bytes: Compressed data
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"""
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if compress == 'none':
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return inf.read()
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comp = COMP_TOOLS.get(compress)
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if not comp:
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raise ValueError(f"Unknown compression algorithm '{compress}'")
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with tempfile.NamedTemporaryFile() as comp_fname:
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with open(comp_fname.name, 'wb') as outf:
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done = False
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for tool in comp.tools.split(','):
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try:
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subprocess.call([tool, '-c'], stdin=inf, stdout=outf)
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done = True
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break
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except FileNotFoundError:
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pass
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if not done:
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raise ValueError(f'Missing tool(s): {comp.tools}\n')
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with open(comp_fname.name, 'rb') as compf:
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comp_data = compf.read()
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return comp_data
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def output_dtb(fsw, seq, fname, arch, compress):
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"""Write out a single devicetree to the FIT
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Args:
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fsw (libfdt.FdtSw): Object to use for writing
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seq (int): Sequence number (1 for first)
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fname (str): Filename containing the DTB
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arch: FIT architecture, e.g. 'arm64'
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compress (str): Compressed algorithm, e.g. 'gzip'
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"""
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with fsw.add_node(f'fdt-{seq}'):
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fsw.property_string('description', os.path.basename(fname))
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fsw.property_string('type', 'flat_dt')
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fsw.property_string('arch', arch)
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fsw.property_string('compression', compress)
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with open(fname, 'rb') as inf:
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compressed = compress_data(inf, compress)
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fsw.property('data', compressed)
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def process_dtb(fname, args):
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"""Process an input DTB, decomposing it if requested and is possible
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Args:
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fname (str): Filename containing the DTB
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args (Namespace): Program arguments
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Returns:
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tuple:
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str: Model name string
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str: Root compatible string
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files: list of filenames corresponding to the DTB
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"""
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# Get the compatible / model information
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with open(fname, 'rb') as inf:
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data = inf.read()
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fdt = libfdt.FdtRo(data)
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model = fdt.getprop(0, 'model').as_str()
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compat = fdt.getprop(0, 'compatible')
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if args.decompose_dtbs:
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# Check if the DTB needs to be decomposed
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path, basename = os.path.split(fname)
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cmd_fname = os.path.join(path, f'.{basename}.cmd')
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with open(cmd_fname, 'r', encoding='ascii') as inf:
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cmd = inf.read()
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if 'scripts/dtc/fdtoverlay' in cmd:
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# This depends on the structure of the composite DTB command
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files = cmd.split()
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files = files[files.index('-i') + 1:]
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else:
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files = [fname]
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else:
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files = [fname]
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return (model, compat, files)
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def build_fit(args):
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"""Build the FIT from the provided files and arguments
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Args:
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args (Namespace): Program arguments
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Returns:
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tuple:
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bytes: FIT data
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int: Number of configurations generated
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size: Total uncompressed size of data
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"""
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seq = 0
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size = 0
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fsw = libfdt.FdtSw()
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setup_fit(fsw, args.name)
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entries = []
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fdts = {}
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# Handle the kernel
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with open(args.kernel, 'rb') as inf:
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comp_data = compress_data(inf, args.compress)
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size += os.path.getsize(args.kernel)
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write_kernel(fsw, comp_data, args)
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for fname in args.dtbs:
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# Ignore non-DTB (*.dtb) files
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if os.path.splitext(fname)[1] != '.dtb':
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continue
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(model, compat, files) = process_dtb(fname, args)
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for fn in files:
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if fn not in fdts:
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seq += 1
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size += os.path.getsize(fn)
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output_dtb(fsw, seq, fn, args.arch, args.compress)
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fdts[fn] = seq
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files_seq = [fdts[fn] for fn in files]
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entries.append([model, compat, files_seq])
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finish_fit(fsw, entries)
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# Include the kernel itself in the returned file count
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return fsw.as_fdt().as_bytearray(), seq + 1, size
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def run_make_fit():
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"""Run the tool's main logic"""
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args = parse_args()
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out_data, count, size = build_fit(args)
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with open(args.output, 'wb') as outf:
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outf.write(out_data)
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ext_fit_size = None
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if args.external:
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mkimage = os.environ.get('MKIMAGE', 'mkimage')
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subprocess.check_call([mkimage, '-E', '-F', args.output],
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stdout=subprocess.DEVNULL)
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with open(args.output, 'rb') as inf:
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data = inf.read()
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ext_fit = libfdt.FdtRo(data)
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ext_fit_size = ext_fit.totalsize()
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if args.verbose:
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comp_size = len(out_data)
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print(f'FIT size {comp_size:#x}/{comp_size / 1024 / 1024:.1f} MB',
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end='')
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if ext_fit_size:
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print(f', header {ext_fit_size:#x}/{ext_fit_size / 1024:.1f} KB',
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end='')
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print(f', {count} files, uncompressed {size / 1024 / 1024:.1f} MB')
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if __name__ == "__main__":
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sys.exit(run_make_fit())
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