diff --git a/machine-learning/ann/ann.py b/machine-learning/ann/ann.py
index a6667d50fb..21f7022a5c 100644
--- a/machine-learning/ann/ann.py
+++ b/machine-learning/ann/ann.py
@@ -65,7 +65,7 @@ class Ann(metaclass=_Singleton):
self.input_shapes: dict[int, tuple[tuple[int], ...]] = {}
self.ann: int | None = None
self.new()
-
+
if self.tuning_file is not None:
# make sure tuning file exists (without clearing contents)
# once filled, the tuning file reduces the cost/time of the first
@@ -105,7 +105,7 @@ class Ann(metaclass=_Singleton):
raise ValueError("model_path must be a file with extension .armnn, .tflite or .onnx")
if not exists(model_path):
raise ValueError("model_path must point to an existing file!")
-
+
save_cached_network = False
if cached_network_path is not None and not exists(cached_network_path):
save_cached_network = True
diff --git a/machine-learning/app/models/constants.py b/machine-learning/app/models/constants.py
index c51dd3b66d..338a481594 100644
--- a/machine-learning/app/models/constants.py
+++ b/machine-learning/app/models/constants.py
@@ -2,53 +2,64 @@ from app.config import clean_name
from app.schemas import ModelSource
_OPENCLIP_MODELS = {
- "RN50__openai",
- "RN50__yfcc15m",
- "RN50__cc12m",
"RN101__openai",
"RN101__yfcc15m",
- "RN50x4__openai",
+ "RN50__cc12m",
+ "RN50__openai",
+ "RN50__yfcc15m",
"RN50x16__openai",
+ "RN50x4__openai",
"RN50x64__openai",
- "ViT-B-32__openai",
+ "ViT-B-16-SigLIP-256__webli",
+ "ViT-B-16-SigLIP-384__webli",
+ "ViT-B-16-SigLIP-512__webli",
+ "ViT-B-16-SigLIP-i18n-256__webli",
+ "ViT-B-16-SigLIP__webli",
+ "ViT-B-16-plus-240__laion400m_e31",
+ "ViT-B-16-plus-240__laion400m_e32",
+ "ViT-B-16__laion400m_e31",
+ "ViT-B-16__laion400m_e32",
+ "ViT-B-16__openai",
+ "ViT-B-32__laion2b-s34b-b79k",
"ViT-B-32__laion2b_e16",
"ViT-B-32__laion400m_e31",
"ViT-B-32__laion400m_e32",
- "ViT-B-32__laion2b-s34b-b79k",
- "ViT-B-16__openai",
- "ViT-B-16__laion400m_e31",
- "ViT-B-16__laion400m_e32",
- "ViT-B-16-plus-240__laion400m_e31",
- "ViT-B-16-plus-240__laion400m_e32",
- "ViT-L-14__openai",
+ "ViT-B-32__openai",
+ "ViT-H-14-378-quickgelu__dfn5b",
+ "ViT-H-14-quickgelu__dfn5b",
+ "ViT-H-14__laion2b-s32b-b79k",
+ "ViT-L-14-336__openai",
+ "ViT-L-14-quickgelu__dfn2b",
+ "ViT-L-14__laion2b-s32b-b82k",
"ViT-L-14__laion400m_e31",
"ViT-L-14__laion400m_e32",
- "ViT-L-14__laion2b-s32b-b82k",
- "ViT-L-14-336__openai",
- "ViT-H-14__laion2b-s32b-b79k",
+ "ViT-L-14__openai",
+ "ViT-L-16-SigLIP-256__webli",
+ "ViT-L-16-SigLIP-384__webli",
+ "ViT-SO400M-14-SigLIP-384__webli",
"ViT-g-14__laion2b-s12b-b42k",
- "ViT-L-14-quickgelu__dfn2b",
- "ViT-H-14-quickgelu__dfn5b",
- "ViT-H-14-378-quickgelu__dfn5b",
+ "XLM-Roberta-Base-ViT-B-32__laion5b_s13b_b90k",
"XLM-Roberta-Large-ViT-H-14__frozen_laion5b_s13b_b90k",
+ "nllb-clip-base-siglip__mrl",
"nllb-clip-base-siglip__v1",
+ "nllb-clip-large-siglip__mrl",
"nllb-clip-large-siglip__v1",
}
_MCLIP_MODELS = {
"LABSE-Vit-L-14",
- "XLM-Roberta-Large-Vit-B-32",
"XLM-Roberta-Large-Vit-B-16Plus",
+ "XLM-Roberta-Large-Vit-B-32",
"XLM-Roberta-Large-Vit-L-14",
}
_INSIGHTFACE_MODELS = {
"antelopev2",
- "buffalo_l",
- "buffalo_m",
"buffalo_s",
+ "buffalo_m",
+ "buffalo_l",
}
diff --git a/machine-learning/export/conda-lock.yml b/machine-learning/export/conda-lock.yml
index 12dc35778e..17578746de 100644
--- a/machine-learning/export/conda-lock.yml
+++ b/machine-learning/export/conda-lock.yml
@@ -5,7 +5,7 @@
# available, unless you explicitly update the lock file.
#
# Install this environment as "YOURENV" with:
-# conda-lock install -n YOURENV --file conda-lock.yml
+# conda-lock install -n YOURENV conda-lock.yml
# To update a single package to the latest version compatible with the version constraints in the source:
# conda-lock lock --lockfile conda-lock.yml --update PACKAGE
# To re-solve the entire environment, e.g. after changing a version constraint in the source file:
@@ -13,13 +13,13 @@
version: 1
metadata:
content_hash:
- linux-64: d42204fa0b65bc7acfc3edfff2d027fb2c395335b1de603909316cf7971a602a
+ linux-64: ceb5c100f77d1cceb7132794f7574e14e198e3bbd864585e4b9ec7034ba73893
channels:
- url: conda-forge
used_env_vars: []
- url: nvidia
used_env_vars: []
- - url: pytorch-nightly
+ - url: pytorch
used_env_vars: []
platforms:
- linux-64
@@ -37,15 +37,892 @@ package:
sha256: fe51de6107f9edc7aa4f786a70f4a883943bc9d39b3bb7307c04c41410990726
category: main
optional: false
-- name: ca-certificates
- version: 2023.7.22
+- name: _openmp_mutex
+ version: '4.5'
+ manager: conda
+ platform: linux-64
+ dependencies:
+ _libgcc_mutex: '0.1'
+ llvm-openmp: '>=9.0.1'
+ url: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-2_kmp_llvm.tar.bz2
+ hash:
+ md5: 562b26ba2e19059551a811e72ab7f793
+ sha256: 84a66275da3a66e3f3e70e9d8f10496d807d01a9e4ec16cd2274cc5e28c478fc
+ category: main
+ optional: false
+- name: _sysroot_linux-64_curr_repodata_hack
+ version: '3'
manager: conda
platform: linux-64
dependencies: {}
- url: https://conda.anaconda.org/conda-forge/linux-64/ca-certificates-2023.7.22-hbcca054_0.conda
+ url: https://conda.anaconda.org/conda-forge/noarch/_sysroot_linux-64_curr_repodata_hack-3-h69a702a_16.conda
hash:
- md5: a73ecd2988327ad4c8f2c331482917f2
- sha256: 525b7b6b5135b952ec1808de84e5eca57c7c7ff144e29ef3e96ae4040ff432c1
+ md5: 1c005af0c6ff22814b7c52ee448d4bea
+ sha256: 6ac30acdbfd3136ee7a1de28af4355165291627e905715611726e674499b0786
+ category: main
+ optional: false
+- name: aiohttp
+ version: 3.9.5
+ manager: conda
+ platform: linux-64
+ dependencies:
+ aiosignal: '>=1.1.2'
+ attrs: '>=17.3.0'
+ frozenlist: '>=1.1.1'
+ libgcc-ng: '>=12'
+ multidict: '>=4.5,<7.0'
+ python: '>=3.11,<3.12.0a0'
+ python_abi: 3.11.*
+ yarl: '>=1.0,<2.0'
+ url: https://conda.anaconda.org/conda-forge/linux-64/aiohttp-3.9.5-py311h459d7ec_0.conda
+ hash:
+ md5: 0175d2636cc41dc019b51462c13ce225
+ sha256: 2eb99d920ef0dcd608e195bb852a64634ecf13f74680796959f1b9d9a9650a7b
+ category: main
+ optional: false
+- name: aiosignal
+ version: 1.3.1
+ manager: conda
+ platform: linux-64
+ dependencies:
+ frozenlist: '>=1.1.0'
+ python: '>=3.7'
+ url: https://conda.anaconda.org/conda-forge/noarch/aiosignal-1.3.1-pyhd8ed1ab_0.tar.bz2
+ hash:
+ md5: d1e1eb7e21a9e2c74279d87dafb68156
+ sha256: 575c742e14c86575986dc867463582a970463da50b77264cdf54df74f5563783
+ category: main
+ optional: false
+- name: aom
+ version: 3.9.1
+ manager: conda
+ platform: linux-64
+ dependencies:
+ libgcc-ng: '>=12'
+ libstdcxx-ng: '>=12'
+ url: https://conda.anaconda.org/conda-forge/linux-64/aom-3.9.1-hac33072_0.conda
+ hash:
+ md5: 346722a0be40f6edc53f12640d301338
+ sha256: b08ef033817b5f9f76ce62dfcac7694e7b6b4006420372de22494503decac855
+ category: main
+ optional: false
+- name: attrs
+ version: 23.2.0
+ manager: conda
+ platform: linux-64
+ dependencies:
+ python: '>=3.7'
+ url: https://conda.anaconda.org/conda-forge/noarch/attrs-23.2.0-pyh71513ae_0.conda
+ hash:
+ md5: 5e4c0743c70186509d1412e03c2d8dfa
+ sha256: 77c7d03bdb243a048fff398cedc74327b7dc79169ebe3b4c8448b0331ea55fea
+ category: main
+ optional: false
+- name: aws-c-auth
+ version: 0.7.22
+ manager: conda
+ platform: linux-64
+ dependencies:
+ __glibc: '>=2.17,<3.0.a0'
+ aws-c-cal: '>=0.7.1,<0.7.2.0a0'
+ aws-c-common: '>=0.9.23,<0.9.24.0a0'
+ aws-c-http: '>=0.8.2,<0.8.3.0a0'
+ aws-c-io: '>=0.14.10,<0.14.11.0a0'
+ aws-c-sdkutils: '>=0.1.16,<0.1.17.0a0'
+ libgcc-ng: '>=12'
+ url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-auth-0.7.22-hbd3ac97_10.conda
+ hash:
+ md5: 7ca4abcc98c7521c02f4e8809bbe40df
+ sha256: c8bf9f9901a56a56b18ab044d67ecde69ee1289881267924dd81670ac34591fe
+ category: main
+ optional: false
+- name: aws-c-cal
+ version: 0.7.1
+ manager: conda
+ platform: linux-64
+ dependencies:
+ __glibc: '>=2.17,<3.0.a0'
+ aws-c-common: '>=0.9.23,<0.9.24.0a0'
+ libgcc-ng: '>=12'
+ openssl: '>=3.3.1,<4.0a0'
+ url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-cal-0.7.1-h87b94db_1.conda
+ hash:
+ md5: 2d76d2cfdcfe2d5c3883d33d8be919e7
+ sha256: f445f38a4170f0ae02cdf13e1bc23cbb826a4b45f39402f02fe5737b0a8ed3a9
+ category: main
+ optional: false
+- name: aws-c-common
+ version: 0.9.23
+ manager: conda
+ platform: linux-64
+ dependencies:
+ libgcc-ng: '>=12'
+ url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-common-0.9.23-h4ab18f5_0.conda
+ hash:
+ md5: 94d61ae2b2b701008a9d52ce6bbead27
+ sha256: f3eab0ec3f01ddc3ebdc235d4ae1b3b803d83e40f2cd2389bf8c65ab96e90f02
+ category: main
+ optional: false
+- name: aws-c-compression
+ version: 0.2.18
+ manager: conda
+ platform: linux-64
+ dependencies:
+ aws-c-common: '>=0.9.23,<0.9.24.0a0'
+ libgcc-ng: '>=12'
+ url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-compression-0.2.18-he027950_7.conda
+ hash:
+ md5: 11e5cb0b426772974f6416545baee0ce
+ sha256: d4c70b8716e19fe56a563ab858ab7440f41c2dd927687357a44e69f23001126d
+ category: main
+ optional: false
+- name: aws-c-event-stream
+ version: 0.4.2
+ manager: conda
+ platform: linux-64
+ dependencies:
+ __glibc: '>=2.17,<3.0.a0'
+ aws-c-common: '>=0.9.23,<0.9.24.0a0'
+ aws-c-io: '>=0.14.10,<0.14.11.0a0'
+ aws-checksums: '>=0.1.18,<0.1.19.0a0'
+ libgcc-ng: '>=12'
+ libstdcxx-ng: '>=12'
+ url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-event-stream-0.4.2-h7671281_15.conda
+ hash:
+ md5: 3b45b0da170f515de8be68155e14955a
+ sha256: b9546f0637c66d4086a169f4210bf0d569140f41c13f0c1c6826355f51f82494
+ category: main
+ optional: false
+- name: aws-c-http
+ version: 0.8.2
+ manager: conda
+ platform: linux-64
+ dependencies:
+ __glibc: '>=2.17,<3.0.a0'
+ aws-c-cal: '>=0.7.1,<0.7.2.0a0'
+ aws-c-common: '>=0.9.23,<0.9.24.0a0'
+ aws-c-compression: '>=0.2.18,<0.2.19.0a0'
+ aws-c-io: '>=0.14.10,<0.14.11.0a0'
+ libgcc-ng: '>=12'
+ url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-http-0.8.2-he17ee6b_6.conda
+ hash:
+ md5: 4e3d1bb2ade85619ac2163e695c2cc1b
+ sha256: c2a9501d5e361051457b0afc3ce77496a73c2cf90ad859010812130d512e9271
+ category: main
+ optional: false
+- name: aws-c-io
+ version: 0.14.10
+ manager: conda
+ platform: linux-64
+ dependencies:
+ __glibc: '>=2.17,<3.0.a0'
+ aws-c-cal: '>=0.7.1,<0.7.2.0a0'
+ aws-c-common: '>=0.9.23,<0.9.24.0a0'
+ libgcc-ng: '>=12'
+ s2n: '>=1.4.17,<1.4.18.0a0'
+ url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-io-0.14.10-h826b7d6_1.conda
+ hash:
+ md5: 6961646dded770513a781de4cd5c1fe1
+ sha256: 68cb6f708e5e1cf50d98f3c896c7a72ab68e71ce9a69be4eea5dbde5c04bebdc
+ category: main
+ optional: false
+- name: aws-c-mqtt
+ version: 0.10.4
+ manager: conda
+ platform: linux-64
+ dependencies:
+ __glibc: '>=2.17,<3.0.a0'
+ aws-c-common: '>=0.9.23,<0.9.24.0a0'
+ aws-c-http: '>=0.8.2,<0.8.3.0a0'
+ aws-c-io: '>=0.14.10,<0.14.11.0a0'
+ libgcc-ng: '>=12'
+ url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-mqtt-0.10.4-hcd6a914_8.conda
+ hash:
+ md5: b81c45867558446640306507498b2c6b
+ sha256: aa6100ed16b1b6eabccca1ee5e36039862e37a7ee91c852de8d4ca0082dcd54e
+ category: main
+ optional: false
+- name: aws-c-s3
+ version: 0.6.0
+ manager: conda
+ platform: linux-64
+ dependencies:
+ __glibc: '>=2.17,<3.0.a0'
+ aws-c-auth: '>=0.7.22,<0.7.23.0a0'
+ aws-c-cal: '>=0.7.1,<0.7.2.0a0'
+ aws-c-common: '>=0.9.23,<0.9.24.0a0'
+ aws-c-http: '>=0.8.2,<0.8.3.0a0'
+ aws-c-io: '>=0.14.10,<0.14.11.0a0'
+ aws-checksums: '>=0.1.18,<0.1.19.0a0'
+ libgcc-ng: '>=12'
+ openssl: '>=3.3.1,<4.0a0'
+ url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-s3-0.6.0-h365ddd8_2.conda
+ hash:
+ md5: 22339cf124753bafda336167f80e7860
+ sha256: 5f82835411b3db3ae9d5db575386d83a8cc6f5f61b414afa6155879b2071c2f6
+ category: main
+ optional: false
+- name: aws-c-sdkutils
+ version: 0.1.16
+ manager: conda
+ platform: linux-64
+ dependencies:
+ aws-c-common: '>=0.9.23,<0.9.24.0a0'
+ libgcc-ng: '>=12'
+ url: https://conda.anaconda.org/conda-forge/linux-64/aws-c-sdkutils-0.1.16-he027950_3.conda
+ hash:
+ md5: adbf0c44ca88a3cded175cd809a106b6
+ sha256: 0f957d8cebe9c9b4041c858ca9a20619eb3fa866c71b21478a02d51f219d59cb
+ category: main
+ optional: false
+- name: aws-checksums
+ version: 0.1.18
+ manager: conda
+ platform: linux-64
+ dependencies:
+ aws-c-common: '>=0.9.23,<0.9.24.0a0'
+ libgcc-ng: '>=12'
+ url: https://conda.anaconda.org/conda-forge/linux-64/aws-checksums-0.1.18-he027950_7.conda
+ hash:
+ md5: 95611b325a9728ed68b8f7eef2dd3feb
+ sha256: 094cff556dbf8fdd60505c8285b0a873de101374f568200275d8fd7fb77ad5e9
+ category: main
+ optional: false
+- name: aws-crt-cpp
+ version: 0.27.3
+ manager: conda
+ platform: linux-64
+ dependencies:
+ __glibc: '>=2.17,<3.0.a0'
+ aws-c-auth: '>=0.7.22,<0.7.23.0a0'
+ aws-c-cal: '>=0.7.1,<0.7.2.0a0'
+ aws-c-common: '>=0.9.23,<0.9.24.0a0'
+ aws-c-event-stream: '>=0.4.2,<0.4.3.0a0'
+ aws-c-http: '>=0.8.2,<0.8.3.0a0'
+ aws-c-io: '>=0.14.10,<0.14.11.0a0'
+ aws-c-mqtt: '>=0.10.4,<0.10.5.0a0'
+ aws-c-s3: '>=0.6.0,<0.6.1.0a0'
+ aws-c-sdkutils: '>=0.1.16,<0.1.17.0a0'
+ libgcc-ng: '>=12'
+ libstdcxx-ng: '>=12'
+ url: https://conda.anaconda.org/conda-forge/linux-64/aws-crt-cpp-0.27.3-hda66527_2.conda
+ hash:
+ md5: 734875312c8196feecc91f89856da612
+ sha256: 3149277f03a55d7dcffdbe489863cacc36a831dbf38b9725bdc653a8c5de134f
+ category: main
+ optional: false
+- name: aws-sdk-cpp
+ version: 1.11.329
+ manager: conda
+ platform: linux-64
+ dependencies:
+ __glibc: '>=2.17,<3.0.a0'
+ aws-c-common: '>=0.9.23,<0.9.24.0a0'
+ aws-c-event-stream: '>=0.4.2,<0.4.3.0a0'
+ aws-checksums: '>=0.1.18,<0.1.19.0a0'
+ aws-crt-cpp: '>=0.27.3,<0.27.4.0a0'
+ libcurl: '>=8.8.0,<9.0a0'
+ libgcc-ng: '>=12'
+ libstdcxx-ng: '>=12'
+ libzlib: '>=1.3.1,<2.0a0'
+ openssl: '>=3.3.1,<4.0a0'
+ url: https://conda.anaconda.org/conda-forge/linux-64/aws-sdk-cpp-1.11.329-h46c3b66_9.conda
+ hash:
+ md5: c840f07ec58dc0b06041e7f36550a539
+ sha256: 983f6977cc6b25c8bc785b20859970009242b3812e6b4de592ceb17caf93acb6
+ category: main
+ optional: false
+- name: azure-core-cpp
+ version: 1.13.0
+ manager: conda
+ platform: linux-64
+ dependencies:
+ __glibc: '>=2.17,<3.0.a0'
+ libcurl: '>=8.8.0,<9.0a0'
+ libgcc-ng: '>=12'
+ libstdcxx-ng: '>=12'
+ openssl: '>=3.3.1,<4.0a0'
+ url: https://conda.anaconda.org/conda-forge/linux-64/azure-core-cpp-1.13.0-h935415a_0.conda
+ hash:
+ md5: debd1677c2fea41eb2233a260f48a298
+ sha256: b7e0a22295db2e1955f89c69cefc32810309b3af66df986d9fb75d89f98a80f7
+ category: main
+ optional: false
+- name: azure-identity-cpp
+ version: 1.8.0
+ manager: conda
+ platform: linux-64
+ dependencies:
+ __glibc: '>=2.17,<3.0.a0'
+ azure-core-cpp: '>=1.13.0,<1.13.1.0a0'
+ libgcc-ng: '>=12'
+ libstdcxx-ng: '>=12'
+ openssl: '>=3.3.1,<4.0a0'
+ url: https://conda.anaconda.org/conda-forge/linux-64/azure-identity-cpp-1.8.0-hd126650_2.conda
+ hash:
+ md5: 36df3cf05459de5d0a41c77c4329634b
+ sha256: f85452eca3ae0e156b1d1a321a1a9f4f58d44ff45236c0d8602ab96aaad3c6ba
+ category: main
+ optional: false
+- name: azure-storage-blobs-cpp
+ version: 12.12.0
+ manager: conda
+ platform: linux-64
+ dependencies:
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platform: linux-64
dependencies: {}
- url: https://conda.anaconda.org/conda-forge/noarch/font-ttf-ubuntu-0.83-hab24e00_0.tar.bz2
+ url: https://conda.anaconda.org/conda-forge/noarch/font-ttf-ubuntu-0.83-h77eed37_2.conda
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platform: linux-64
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- url: https://conda.anaconda.org/conda-forge/noarch/kernel-headers_linux-64-2.6.32-he073ed8_16.conda
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+ libzlib: '>=1.2.13,<2.0.0a0'
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-- name: ld_impl_linux-64
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platform: linux-64
- dependencies: {}
- url: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.40-h41732ed_0.conda
+ dependencies:
+ fonts-conda-forge: ''
+ url: https://conda.anaconda.org/conda-forge/noarch/fonts-conda-ecosystem-1-0.tar.bz2
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-- name: tzdata
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category: main
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category: main
optional: false
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- url: https://conda.anaconda.org/conda-forge/noarch/sysroot_linux-64-2.12-he073ed8_16.conda
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- url: https://conda.anaconda.org/conda-forge/noarch/fonts-conda-ecosystem-1-0.tar.bz2
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platform: linux-64
dependencies:
libgcc-ng: '>=12'
- libstdcxx-ng: '>=12'
- url: https://conda.anaconda.org/conda-forge/linux-64/aom-3.6.1-h59595ed_0.conda
+ libpng: '>=1.6.39,<1.7.0a0'
+ libzlib: '>=1.2.13,<2.0.0a0'
+ url: https://conda.anaconda.org/conda-forge/linux-64/freetype-2.12.1-h267a509_2.conda
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optional: false
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category: main
optional: false
-- name: gettext
- version: 0.21.1
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manager: conda
platform: linux-64
dependencies:
libgcc-ng: '>=12'
- url: https://conda.anaconda.org/conda-forge/linux-64/gettext-0.21.1-h27087fc_0.tar.bz2
+ python: '>=3.11,<3.12.0a0'
+ python_abi: 3.11.*
+ url: https://conda.anaconda.org/conda-forge/linux-64/frozenlist-1.4.1-py311h459d7ec_0.conda
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+ dependencies:
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+ url: https://conda.anaconda.org/conda-forge/noarch/fsspec-2024.5.0-pyhff2d567_0.conda
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+ dependencies:
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+ wcwidth: '>=0.2.5'
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+ url: https://conda.anaconda.org/conda-forge/linux-64/gcc-12.4.0-h236703b_0.conda
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+ libstdcxx-ng: '>=12.4.0'
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+ url: https://conda.anaconda.org/conda-forge/linux-64/gcc_impl_linux-64-12.4.0-hb2e57f8_0.conda
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+ manager: conda
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+ libasprintf: 0.22.5
+ libasprintf-devel: 0.22.5
+ libgcc-ng: '>=12'
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+ libgettextpo-devel: 0.22.5
+ libstdcxx-ng: '>=12'
+ url: https://conda.anaconda.org/conda-forge/linux-64/gettext-0.22.5-h59595ed_2.conda
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category: main
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-- name: gmp
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- libstdcxx-ng: '>=7.5.0'
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+ gflags: '>=2.2.2,<2.3.0a0'
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+ libstdcxx-ng: '>=12'
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category: main
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optional: false
- name: libabseil
- version: '20230802.1'
+ version: '20240116.2'
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+ libgcc-ng: '>=12'
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manager: conda
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sha256: fd1d153962764433fe6233f34a72cdeed5dcf8a883a85769e8295ce940b5b0c5
category: main
optional: false
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+ url: https://conda.anaconda.org/nvidia/linux-64/libcublas-12.4.2.65-0.tar.bz2
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+ manager: conda
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+ url: https://conda.anaconda.org/nvidia/linux-64/libcufft-11.2.0.44-0.tar.bz2
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+ sha256: 4a2040bd5d425dfaa53d43423ed28a54eb4ae8a637686e7fdc877681b7b99237
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+ url: https://conda.anaconda.org/nvidia/linux-64/libcufile-1.9.1.3-0.tar.bz2
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+ libgcc-ng: '>=12'
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+ zstd: '>=1.5.6,<1.6.0a0'
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+ url: https://conda.anaconda.org/nvidia/linux-64/libcusparse-12.3.0.142-0.tar.bz2
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- version: '1.19'
+ version: '1.20'
manager: conda
platform: linux-64
dependencies:
libgcc-ng: '>=12'
- url: https://conda.anaconda.org/conda-forge/linux-64/libdeflate-1.19-hd590300_0.conda
+ url: https://conda.anaconda.org/conda-forge/linux-64/libdeflate-1.20-hd590300_0.conda
hash:
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+ category: main
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+ manager: conda
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+ dependencies:
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+ libpciaccess: '>=0.18,<0.19.0a0'
+ url: https://conda.anaconda.org/conda-forge/linux-64/libdrm-2.4.122-h4ab18f5_0.conda
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+ category: main
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+ manager: conda
+ platform: linux-64
+ dependencies:
+ libgcc-ng: '>=7.5.0'
+ ncurses: '>=6.2,<7.0.0a0'
+ url: https://conda.anaconda.org/conda-forge/linux-64/libedit-3.1.20191231-he28a2e2_2.tar.bz2
+ hash:
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platform: linux-64
dependencies:
- libgcc-ng: '>=7.5.0'
- url: https://conda.anaconda.org/conda-forge/linux-64/libev-4.33-h516909a_1.tar.bz2
+ libgcc-ng: '>=12'
+ url: https://conda.anaconda.org/conda-forge/linux-64/libev-4.33-hd590300_2.conda
hash:
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category: main
optional: false
-- name: libexpat
- version: 2.5.0
+- name: libevent
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manager: conda
platform: linux-64
dependencies:
libgcc-ng: '>=12'
- url: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.5.0-hcb278e6_1.conda
+ openssl: '>=3.1.1,<4.0a0'
+ url: https://conda.anaconda.org/conda-forge/linux-64/libevent-2.1.12-hf998b51_1.conda
hash:
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+ category: main
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+- name: libexpat
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+ manager: conda
+ platform: linux-64
+ dependencies:
+ libgcc-ng: '>=12'
+ url: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.6.2-h59595ed_0.conda
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category: main
optional: false
-- name: libgfortran5
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+ version: 12.4.0
manager: conda
platform: linux-64
dependencies:
- libgcc-ng: '>=13.2.0'
- url: https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-13.2.0-ha4646dd_2.conda
+ __unix: ''
+ url: https://conda.anaconda.org/conda-forge/noarch/libgcc-devel_linux-64-12.4.0-ha4f9413_100.conda
hash:
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+ manager: conda
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+ dependencies:
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+ _openmp_mutex: '>=4.5'
+ url: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-14.1.0-h77fa898_0.conda
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+ category: main
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+ manager: conda
+ platform: linux-64
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+ manager: conda
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+ dependencies:
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+ libgettextpo: 0.22.5
+ url: https://conda.anaconda.org/conda-forge/linux-64/libgettextpo-devel-0.22.5-h59595ed_2.conda
+ hash:
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+ url: https://conda.anaconda.org/conda-forge/linux-64/libgfortran-ng-14.1.0-h69a702a_0.conda
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+ pcre2: '>=10.44,<10.45.0a0'
+ url: https://conda.anaconda.org/conda-forge/linux-64/libglib-2.80.3-h8a4344b_1.conda
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+ category: main
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+ manager: conda
+ platform: linux-64
+ dependencies:
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+ url: https://conda.anaconda.org/conda-forge/linux-64/libgomp-14.1.0-h77fa898_0.conda
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+ category: main
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+ url: https://conda.anaconda.org/conda-forge/linux-64/libgoogle-cloud-2.26.0-h26d7fe4_0.conda
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+ category: main
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+ manager: conda
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+ libgcc-ng: '>=12'
+ libgoogle-cloud: 2.26.0
+ libstdcxx-ng: '>=12'
+ libzlib: '>=1.3.1,<2.0a0'
+ openssl: ''
+ url: https://conda.anaconda.org/conda-forge/linux-64/libgoogle-cloud-storage-2.26.0-ha262f82_0.conda
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+ category: main
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+ manager: conda
+ platform: linux-64
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+ libabseil: '>=20240116.1,<20240117.0a0'
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+ libprotobuf: '>=4.25.3,<4.25.4.0a0'
+ libre2-11: '>=2023.9.1,<2024.0a0'
+ libstdcxx-ng: '>=12'
+ libzlib: '>=1.2.13,<2.0.0a0'
+ openssl: '>=3.2.1,<4.0a0'
+ re2: ''
+ url: https://conda.anaconda.org/conda-forge/linux-64/libgrpc-1.62.2-h15f2491_0.conda
+ hash:
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+ sha256: 28241ed89335871db33cb6010e9ccb2d9e9b6bb444ddf6884f02f0857363c06a
+ category: main
+ optional: false
+- name: libhwloc
+ version: 2.11.1
+ manager: conda
+ platform: linux-64
+ dependencies:
+ __glibc: '>=2.17,<3.0.a0'
+ libgcc-ng: '>=12'
+ libstdcxx-ng: '>=12'
+ libxml2: '>=2.12.7,<3.0a0'
+ url: https://conda.anaconda.org/conda-forge/linux-64/libhwloc-2.11.1-default_hecaa2ac_1000.conda
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category: main
optional: false
- name: libiconv
@@ -582,11 +2071,25 @@ package:
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platform: linux-64
dependencies:
- libgcc-ng: '>=10.3.0'
- url: https://conda.anaconda.org/conda-forge/linux-64/libiconv-1.17-h166bdaf_0.tar.bz2
+ libgcc-ng: '>=12'
+ url: https://conda.anaconda.org/conda-forge/linux-64/libiconv-1.17-hd590300_2.conda
hash:
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+ sha256: 8ac2f6a9f186e76539439e50505d98581472fedb347a20e7d1f36429849f05c9
+ category: main
+ optional: false
+- name: libidn2
+ version: 2.3.7
+ manager: conda
+ platform: linux-64
+ dependencies:
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+ libgcc-ng: '>=12'
+ libunistring: '>=0,<1.0a0'
+ url: https://conda.anaconda.org/conda-forge/linux-64/libidn2-2.3.7-hd590300_0.conda
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category: main
optional: false
- name: libjpeg-turbo
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sha256: b954e09b7e49c2f2433d6f3bb73868eda5e378278b0f8c1dd10a7ef090e14f2f
category: main
optional: false
+- name: liblapack
+ version: 3.9.0
+ manager: conda
+ platform: linux-64
+ dependencies:
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+ url: https://conda.anaconda.org/conda-forge/linux-64/liblapack-3.9.0-16_linux64_mkl.tar.bz2
+ hash:
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+ sha256: d6201f860b2d76ed59027e69c2bbad6d1cb211a215ec9705cc487cde488fa1fa
+ category: main
+ optional: false
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+ version: 3.9.0
+ manager: conda
+ platform: linux-64
+ dependencies:
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+ libcblas: 3.9.0
+ liblapack: 3.9.0
+ url: https://conda.anaconda.org/conda-forge/linux-64/liblapacke-3.9.0-16_linux64_mkl.tar.bz2
+ hash:
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+ manager: conda
+ platform: linux-64
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+ libstdcxx-ng: '>=12'
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+ openssl: '>=3.2.0,<4.0a0'
+ url: https://conda.anaconda.org/conda-forge/linux-64/libnghttp2-1.58.0-h47da74e_1.conda
+ hash:
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+ category: main
+ optional: false
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+ version: 12.2.5.2
+ manager: conda
+ platform: linux-64
+ dependencies: {}
+ url: https://conda.anaconda.org/nvidia/linux-64/libnpp-12.2.5.2-0.tar.bz2
+ hash:
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version: 2.0.1
manager: conda
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category: main
optional: false
-- name: libnuma
- version: 2.0.16
+- name: libnvfatbin
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+ manager: conda
+ platform: linux-64
+ dependencies: {}
+ url: https://conda.anaconda.org/nvidia/linux-64/libnvfatbin-12.4.127-0.tar.bz2
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- sha256: d6201f860b2d76ed59027e69c2bbad6d1cb211a215ec9705cc487cde488fa1fa
- category: main
- optional: false
-- name: aws-sdk-cpp
- version: 1.11.182
- manager: conda
- platform: linux-64
- dependencies:
- aws-c-common: '>=0.9.4,<0.9.5.0a0'
- aws-c-event-stream: '>=0.3.2,<0.3.3.0a0'
- aws-checksums: '>=0.1.17,<0.1.18.0a0'
- aws-crt-cpp: '>=0.24.4,<0.24.5.0a0'
- libcurl: '>=8.4.0,<9.0a0'
- libgcc-ng: '>=12'
- libstdcxx-ng: '>=12'
- libzlib: '>=1.2.13,<1.3.0a0'
- openssl: '>=3.1.4,<4.0a0'
- url: https://conda.anaconda.org/conda-forge/linux-64/aws-sdk-cpp-1.11.182-hb97d603_2.conda
- hash:
- md5: 4b28dbada9459f1d89c77939b9284388
- sha256: d82ab8ee4babb48879f1971d70a5e90926cf784ac6e403c580bc0eb315736d34
- category: main
- optional: false
-- name: ffmpeg
- version: 6.0.0
- manager: conda
- platform: linux-64
- dependencies:
- aom: '>=3.6.1,<3.7.0a0'
- bzip2: '>=1.0.8,<2.0a0'
- dav1d: '>=1.2.1,<1.2.2.0a0'
- fontconfig: '>=2.14.2,<3.0a0'
- fonts-conda-ecosystem: ''
- freetype: '>=2.12.1,<3.0a0'
- gmp: '>=6.2.1,<7.0a0'
- gnutls: '>=3.7.8,<3.8.0a0'
- lame: '>=3.100,<3.101.0a0'
- libass: '>=0.17.1,<0.17.2.0a0'
- libgcc-ng: '>=12'
- libopus: '>=1.3.1,<2.0a0'
- libstdcxx-ng: '>=12'
- libva: '>=2.20.0,<3.0a0'
- libvpx: '>=1.13.0,<1.14.0a0'
- libxml2: '>=2.11.5,<2.12.0a0'
- libzlib: '>=1.2.13,<1.3.0a0'
- openh264: '>=2.3.1,<2.3.2.0a0'
- svt-av1: '>=1.7.0,<1.7.1.0a0'
- x264: '>=1!164.3095,<1!165'
- x265: '>=3.5,<3.6.0a0'
- url: https://conda.anaconda.org/conda-forge/linux-64/ffmpeg-6.0.0-gpl_h334edf3_105.conda
- hash:
- md5: d47c3e10d2ca5fc07107d4ac640603da
- sha256: f1f9070190bc189b9ec9034e9d9adbbb530cd25b571c763b33585195c0e13813
- category: main
- optional: false
-- name: liblapacke
- version: 3.9.0
- manager: conda
- platform: linux-64
- dependencies:
- libblas: 3.9.0
- libcblas: 3.9.0
- liblapack: 3.9.0
- url: https://conda.anaconda.org/conda-forge/linux-64/liblapacke-3.9.0-16_linux64_mkl.tar.bz2
- hash:
- md5: 44ccc4d4dca6a8d57fa17442bc64b5a1
- sha256: 935036dc46c483cba8288c6de58d461ab3f42915715ffe9485105ad1dd203a0e
- category: main
- optional: false
-- name: numpy
- version: 1.26.0
- manager: conda
- platform: linux-64
- dependencies:
- libblas: '>=3.9.0,<4.0a0'
- libcblas: '>=3.9.0,<4.0a0'
- libgcc-ng: '>=12'
- liblapack: '>=3.9.0,<4.0a0'
- libstdcxx-ng: '>=12'
- python: '>=3.11,<3.12.0a0'
- python_abi: 3.11.*
- url: https://conda.anaconda.org/conda-forge/linux-64/numpy-1.26.0-py311h64a7726_0.conda
- hash:
- md5: bf16a9f625126e378302f08e7ed67517
- sha256: 0aab5cef67cc2a1cd584f6e9cc6f2065c7a28c142d7defcb8096e8f719d9b3bf
- category: main
- optional: false
-- name: tokenizers
- version: 0.14.1
- manager: conda
- platform: linux-64
- dependencies:
- huggingface_hub: '>=0.16.4,<0.18'
- libgcc-ng: '>=12'
- libstdcxx-ng: '>=12'
- openssl: '>=3.1.3,<4.0a0'
- python: '>=3.11,<3.12.0a0'
- python_abi: 3.11.*
- url: https://conda.anaconda.org/conda-forge/linux-64/tokenizers-0.14.1-py311h6640629_2.conda
- hash:
- md5: abef7be15a5487d8bd1b877f16aedf82
- sha256: 7d9338ccc698685307d87dcadfdf6c30e0795cd8fa6e55be16c9e4822aa0eba6
- category: main
- optional: false
-- name: blas-devel
- version: 3.9.0
- manager: conda
- platform: linux-64
- dependencies:
- libblas: 3.9.0
- libcblas: 3.9.0
- liblapack: 3.9.0
- liblapacke: 3.9.0
- mkl: '>=2022.1.0,<2023.0a0'
- mkl-devel: 2022.1.*
- url: https://conda.anaconda.org/conda-forge/linux-64/blas-devel-3.9.0-16_linux64_mkl.tar.bz2
- hash:
- md5: 3f92c1c9e1c0e183462c5071aa02cae1
- sha256: a7da65ca4e0322317cbc4d387c4a5f075cdc7fcd12ad9f7f18da758c7532749a
- category: main
- optional: false
-- name: libarrow
- version: 13.0.0
- manager: conda
- platform: linux-64
- dependencies:
- aws-crt-cpp: '>=0.24.4,<0.24.5.0a0'
- aws-sdk-cpp: '>=1.11.182,<1.11.183.0a0'
- bzip2: '>=1.0.8,<2.0a0'
- glog: '>=0.6.0,<0.7.0a0'
- libabseil: '>=20230802.1,<20230803.0a0'
- libbrotlidec: '>=1.1.0,<1.2.0a0'
- libbrotlienc: '>=1.1.0,<1.2.0a0'
- libgcc-ng: '>=12'
- libgoogle-cloud: '>=2.12.0,<2.13.0a0'
- libgrpc: '>=1.58.1,<1.59.0a0'
- libprotobuf: '>=4.24.3,<4.24.4.0a0'
- libre2-11: '>=2023.6.2,<2024.0a0'
- libstdcxx-ng: '>=12'
- libthrift: '>=0.19.0,<0.19.1.0a0'
- libutf8proc: '>=2.8.0,<3.0a0'
- libzlib: '>=1.2.13,<1.3.0a0'
- lz4-c: '>=1.9.3,<1.10.0a0'
- openssl: '>=3.1.4,<4.0a0'
- orc: '>=1.9.0,<1.9.1.0a0'
- re2: ''
- snappy: '>=1.1.10,<2.0a0'
- ucx: '>=1.15.0,<1.16.0a0'
- zstd: '>=1.5.5,<1.6.0a0'
- url: https://conda.anaconda.org/conda-forge/linux-64/libarrow-13.0.0-hecbb4c5_13_cpu.conda
- hash:
- md5: 71172fd3f165406793843c3211248169
- sha256: 627694b001dd6f27618311d6769967da23181a5cabe373f4f6d70b5f34c704a8
- category: main
- optional: false
-- name: onnx
- version: 1.14.1
- manager: conda
- platform: linux-64
- dependencies:
- libgcc-ng: '>=12'
- libprotobuf: '>=4.24.3,<4.24.4.0a0'
- libstdcxx-ng: '>=12'
- numpy: '>=1.23.5,<2.0a0'
- protobuf: ''
- python: '>=3.11,<3.12.0a0'
- python_abi: 3.11.*
- typing-extensions: '>=3.6.2.1'
- url: https://conda.anaconda.org/conda-forge/linux-64/onnx-1.14.1-py311h0f0ab71_3.conda
- hash:
- md5: fc47944dd5840f6fee04c8da7ebdc84a
- sha256: fe58d2b64cd717732e6ae8e734bb628fb82a3276b37fc36f28d3d80166389c0b
- category: main
- optional: false
-- name: onnxruntime
- version: 1.16.1
- manager: conda
- platform: linux-64
- dependencies:
- coloredlogs: ''
- libgcc-ng: '>=12'
- libstdcxx-ng: '>=12'
- numpy: '>=1.23.5,<2.0a0'
- packaging: ''
- protobuf: ''
- python: '>=3.11,<3.12.0a0'
- python-flatbuffers: ''
- python_abi: 3.11.*
- sympy: ''
- url: https://conda.anaconda.org/conda-forge/linux-64/onnxruntime-1.16.1-py311hf017ac3_0_cpu.conda
- hash:
- md5: 084207bdc127f632e8b191719d1521b6
- sha256: d1044c3403fa3502084a662d6f254a1573fc813d4041fcba974b995bda4888c8
- category: main
- optional: false
-- name: pandas
- version: 2.1.2
+- name: zstd
+ version: 1.5.6
manager: conda
platform: linux-64
dependencies:
libgcc-ng: '>=12'
libstdcxx-ng: '>=12'
- numpy: '>=1.23.5,<2.0a0'
- python: '>=3.11,<3.12.0a0'
- python-dateutil: '>=2.8.1'
- python-tzdata: '>=2022a'
- python_abi: 3.11.*
- pytz: '>=2020.1'
- url: https://conda.anaconda.org/conda-forge/linux-64/pandas-2.1.2-py311h320fe9a_0.conda
+ libzlib: '>=1.2.13,<2.0.0a0'
+ url: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.6-ha6fb4c9_0.conda
hash:
- md5: c36a53056129665b34db419b6af3d230
- sha256: 7e21fef8bf9492c9e39daa21f82204672bd87e8ae16a95964f41052b71e562e3
- category: main
- optional: false
-- name: blas
- version: '2.116'
- manager: conda
- platform: linux-64
- dependencies:
- _openmp_mutex: '>=4.5'
- blas-devel: 3.9.0
- libblas: 3.9.0
- libcblas: 3.9.0
- libgcc-ng: '>=12'
- libgfortran-ng: ''
- libgfortran5: '>=10.4.0'
- liblapack: 3.9.0
- liblapacke: 3.9.0
- llvm-openmp: '>=14.0.4'
- url: https://conda.anaconda.org/conda-forge/linux-64/blas-2.116-mkl.tar.bz2
- hash:
- md5: c196a26abf6b4f132c88828ab7c2231c
- sha256: 87056ebdc90b6d1ea6726d04d42b844cc302112e80508edbf7bf1f1a4fd3fed2
- category: main
- optional: false
-- name: pyarrow
- version: 13.0.0
- manager: conda
- platform: linux-64
- dependencies:
- libarrow: 13.0.0
- libgcc-ng: '>=12'
- libstdcxx-ng: '>=12'
- numpy: '>=1.23.5,<2.0a0'
- python: '>=3.11,<3.12.0a0'
- python_abi: 3.11.*
- url: https://conda.anaconda.org/conda-forge/linux-64/pyarrow-13.0.0-py311h39c9aba_13_cpu.conda
- hash:
- md5: 9b9c895aa2414d8c27e2e7818d13bef7
- sha256: 701fe1491a3806cadfadd5133add1f3e19e25de4d0afad7935c841882758c1d9
- category: main
- optional: false
-- name: datasets
- version: 2.14.6
- manager: conda
- platform: linux-64
- dependencies:
- aiohttp: ''
- dill: '>=0.3.0,<0.3.8'
- fsspec: '>=2023.1.0,<=2023.10.0'
- huggingface_hub: '>=0.14.0,<1.0.0'
- importlib-metadata: ''
- multiprocess: ''
- numpy: '>=1.17'
- packaging: ''
- pandas: ''
- pyarrow: '>=8.0.0'
- python: '>=3.8.0'
- python-xxhash: ''
- pyyaml: '>=5.1'
- requests: '>=2.19.0'
- tqdm: '>=4.62.1'
- url: https://conda.anaconda.org/conda-forge/noarch/datasets-2.14.6-pyhd8ed1ab_0.conda
- hash:
- md5: 0e011ab75c4c93d15668368b4b0e0111
- sha256: fe6d93c4260c70817b9b31e178acb94562d6831bacbab3f771f5733008db6719
- category: main
- optional: false
-- name: pytorch
- version: 2.2.0.dev20231028
- manager: conda
- platform: linux-64
- dependencies:
- blas: '*'
- filelock: ''
- jinja2: ''
- llvm-openmp: <16
- mkl: '>=2018'
- networkx: ''
- python: '>=3.11,<3.12.0a0'
- pytorch-mutex: '1.0'
- pyyaml: ''
- sympy: ''
- typing_extensions: ''
- url: https://conda.anaconda.org/pytorch-nightly/linux-64/pytorch-2.2.0.dev20231028-py3.11_cpu_0.tar.bz2
- hash:
- md5: 24f4eacf75c41cfb75212b20c732b5e7
- sha256: 59d772e48c4522b42ccd258b68876586c35ab83820c3c769ed752f630cc207f6
- category: main
- optional: false
-- name: torchvision
- version: 0.17.0.dev20231028
- manager: conda
- platform: linux-64
- dependencies:
- ffmpeg: '>=4.2'
- libjpeg-turbo: ''
- libpng: ''
- numpy: '>=1.23.5'
- pillow: '>=5.3.0,!=8.3.*'
- python: '>=3.11,<3.12.0a0'
- pytorch: 2.2.0.dev20231028
- pytorch-mutex: '1.0'
- requests: ''
- url: https://conda.anaconda.org/pytorch-nightly/linux-64/torchvision-0.17.0.dev20231028-py311_cpu.tar.bz2
- hash:
- md5: 1d02d809860d49d10f618dbbb23ada89
- sha256: c580064c2c3de5447b58e7c22c8b6df3aaf4ee0249456677ebe1426067b93954
- category: main
- optional: false
-- name: transformers
- version: 4.34.1
- manager: conda
- platform: linux-64
- dependencies:
- dataclasses: ''
- datasets: '!=2.5.0'
- filelock: ''
- huggingface_hub: ''
- importlib_metadata: ''
- numpy: '>=1.17'
- packaging: '>=20.0'
- python: '>=3.7'
- pyyaml: ''
- regex: '!=2019.12.17'
- requests: ''
- sacremoses: ''
- safetensors: '>=0.3.1'
- tokenizers: '>=0.14,<0.15'
- tqdm: '>=4.27'
- url: https://conda.anaconda.org/conda-forge/noarch/transformers-4.34.1-pyhd8ed1ab_0.conda
- hash:
- md5: 56eff02cf489a3324fdfc69b486e8d32
- sha256: b50103b6d7f216e2558a513c9144195c3d6102efeae6188500b1b796977d31dd
- category: main
- optional: false
-- name: timm
- version: 0.9.8
- manager: conda
- platform: linux-64
- dependencies:
- huggingface_hub: ''
- python: '>=3.7'
- pytorch: '>=1.7'
- pyyaml: ''
- safetensors: ''
- torchvision: ''
- url: https://conda.anaconda.org/conda-forge/noarch/timm-0.9.8-pyhd8ed1ab_0.conda
- hash:
- md5: 2510ec2ba4815361ae94988955bab32d
- sha256: 583496b71c85646450096d3166b4d555efcaa1043affb3df2017e5c160122bd4
- category: main
- optional: false
-- name: open-clip-torch
- version: 2.23.0
- manager: conda
- platform: linux-64
- dependencies:
- ftfy: ''
- huggingface_hub: ''
- protobuf: ''
- python: '>=3.7'
- pytorch: '>=1.9.0'
- regex: ''
- sentencepiece: ''
- timm: ''
- torchvision: ''
- tqdm: ''
- url: https://conda.anaconda.org/conda-forge/noarch/open-clip-torch-2.23.0-pyhd8ed1ab_1.conda
- hash:
- md5: b1aae9defe28b83e8f48db34ac25d1d6
- sha256: 50886e8ed3b78ac90e3729141edd4fdf8374bd7f34eda7a6d215f5faa0ce339f
+ md5: 4d056880988120e29d75bfff282e0f45
+ sha256: c558b9cc01d9c1444031bd1ce4b9cff86f9085765f17627a6cd85fc623c8a02b
category: main
optional: false
- name: multilingual-clip
@@ -3506,15 +4314,15 @@ package:
sha256: b9acf95b8309c85a0db5e9c88c5f1b400687e08d72408c460731ae31e71dc73a
category: main
optional: false
-- name: onnx-simplifier
- version: 0.4.35
+- name: onnxsim
+ version: 0.4.36
manager: pip
platform: linux-64
dependencies:
onnx: '*'
rich: '*'
- url: https://files.pythonhosted.org/packages/5f/b3/b953aa4d877661c66e626fdd57830b4e217b45b0139ba6d5e0f38a663b1c/onnx_simplifier-0.4.35-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
+ url: https://files.pythonhosted.org/packages/db/94/22aab761b3d416bce02020d9ca98dc692427c2717b0325952e30ce41f83b/onnxsim-0.4.36-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
hash:
- sha256: 4986c4272440e719d0652c3bbecba5d842ae2ddb7de7804f23c781761e11cc8a
+ sha256: fa7596e6b806ed19077f7652788a50ee576c172b4d16d421f0593aef1a6fa4c4
category: main
optional: false
diff --git a/machine-learning/export/env.yaml b/machine-learning/export/env.yaml
index f7144812d0..27fb72098e 100644
--- a/machine-learning/export/env.yaml
+++ b/machine-learning/export/env.yaml
@@ -2,7 +2,7 @@ name: base
channels:
- conda-forge
- nvidia
- - pytorch-nightly
+ - pytorch
platforms:
- linux-64
dependencies:
@@ -13,7 +13,7 @@ dependencies:
- orjson==3.*
- pip
- python==3.11.*
- - pytorch
+ - pytorch>=2.3
- rich==13.*
- safetensors==0.*
- setuptools==68.*
@@ -21,5 +21,5 @@ dependencies:
- transformers==4.*
- pip:
- multilingual-clip
- - onnx-simplifier
+ - onnxsim
category: main
diff --git a/machine-learning/export/models/mclip.py b/machine-learning/export/models/mclip.py
index 565539016a..06324e490d 100644
--- a/machine-learning/export/models/mclip.py
+++ b/machine-learning/export/models/mclip.py
@@ -1,3 +1,4 @@
+import os
import tempfile
import warnings
from pathlib import Path
@@ -8,7 +9,6 @@ from transformers import AutoTokenizer
from .openclip import OpenCLIPModelConfig
from .openclip import to_onnx as openclip_to_onnx
-from .optimize import optimize
from .util import get_model_path
_MCLIP_TO_OPENCLIP = {
@@ -23,18 +23,20 @@ def to_onnx(
model_name: str,
output_dir_visual: Path | str,
output_dir_textual: Path | str,
-) -> None:
+) -> tuple[Path, Path]:
textual_path = get_model_path(output_dir_textual)
with tempfile.TemporaryDirectory() as tmpdir:
- model = MultilingualCLIP.from_pretrained(model_name, cache_dir=tmpdir)
+ model = MultilingualCLIP.from_pretrained(model_name, cache_dir=os.environ.get("CACHE_DIR", tmpdir))
AutoTokenizer.from_pretrained(model_name).save_pretrained(output_dir_textual)
+ model.eval()
for param in model.parameters():
param.requires_grad_(False)
export_text_encoder(model, textual_path)
- openclip_to_onnx(_MCLIP_TO_OPENCLIP[model_name], output_dir_visual)
- optimize(textual_path)
+ visual_path, _ = openclip_to_onnx(_MCLIP_TO_OPENCLIP[model_name], output_dir_visual)
+ assert visual_path is not None, "Visual model export failed"
+ return visual_path, textual_path
def export_text_encoder(model: MultilingualCLIP, output_path: Path | str) -> None:
@@ -58,10 +60,10 @@ def export_text_encoder(model: MultilingualCLIP, output_path: Path | str) -> Non
args,
output_path.as_posix(),
input_names=["input_ids", "attention_mask"],
- output_names=["text_embedding"],
+ output_names=["embedding"],
opset_version=17,
- dynamic_axes={
- "input_ids": {0: "batch_size", 1: "sequence_length"},
- "attention_mask": {0: "batch_size", 1: "sequence_length"},
- },
+ # dynamic_axes={
+ # "input_ids": {0: "batch_size", 1: "sequence_length"},
+ # "attention_mask": {0: "batch_size", 1: "sequence_length"},
+ # },
)
diff --git a/machine-learning/export/models/openclip.py b/machine-learning/export/models/openclip.py
index d5d2b3ef5d..68a4b90353 100644
--- a/machine-learning/export/models/openclip.py
+++ b/machine-learning/export/models/openclip.py
@@ -1,3 +1,4 @@
+import os
import tempfile
import warnings
from dataclasses import dataclass, field
@@ -7,7 +8,6 @@ import open_clip
import torch
from transformers import AutoTokenizer
-from .optimize import optimize
from .util import get_model_path, save_config
@@ -23,25 +23,28 @@ class OpenCLIPModelConfig:
if open_clip_cfg is None:
raise ValueError(f"Unknown model {self.name}")
self.image_size = open_clip_cfg["vision_cfg"]["image_size"]
- self.sequence_length = open_clip_cfg["text_cfg"]["context_length"]
+ self.sequence_length = open_clip_cfg["text_cfg"].get("context_length", 77)
def to_onnx(
model_cfg: OpenCLIPModelConfig,
output_dir_visual: Path | str | None = None,
output_dir_textual: Path | str | None = None,
-) -> None:
+) -> tuple[Path | None, Path | None]:
+ visual_path = None
+ textual_path = None
with tempfile.TemporaryDirectory() as tmpdir:
model = open_clip.create_model(
model_cfg.name,
pretrained=model_cfg.pretrained,
jit=False,
- cache_dir=tmpdir,
+ cache_dir=os.environ.get("CACHE_DIR", tmpdir),
require_pretrained=True,
)
text_vision_cfg = open_clip.get_model_config(model_cfg.name)
+ model.eval()
for param in model.parameters():
param.requires_grad_(False)
@@ -53,8 +56,6 @@ def to_onnx(
save_config(text_vision_cfg, output_dir_visual.parent / "config.json")
export_image_encoder(model, model_cfg, visual_path)
- optimize(visual_path)
-
if output_dir_textual is not None:
output_dir_textual = Path(output_dir_textual)
textual_path = get_model_path(output_dir_textual)
@@ -62,7 +63,7 @@ def to_onnx(
tokenizer_name = text_vision_cfg["text_cfg"].get("hf_tokenizer_name", "openai/clip-vit-base-patch32")
AutoTokenizer.from_pretrained(tokenizer_name).save_pretrained(output_dir_textual)
export_text_encoder(model, model_cfg, textual_path)
- optimize(textual_path)
+ return visual_path, textual_path
def export_image_encoder(model: open_clip.CLIP, model_cfg: OpenCLIPModelConfig, output_path: Path | str) -> None:
@@ -83,9 +84,9 @@ def export_image_encoder(model: open_clip.CLIP, model_cfg: OpenCLIPModelConfig,
args,
output_path.as_posix(),
input_names=["image"],
- output_names=["image_embedding"],
+ output_names=["embedding"],
opset_version=17,
- dynamic_axes={"image": {0: "batch_size"}},
+ # dynamic_axes={"image": {0: "batch_size"}},
)
@@ -107,7 +108,7 @@ def export_text_encoder(model: open_clip.CLIP, model_cfg: OpenCLIPModelConfig, o
args,
output_path.as_posix(),
input_names=["text"],
- output_names=["text_embedding"],
+ output_names=["embedding"],
opset_version=17,
- dynamic_axes={"text": {0: "batch_size"}},
+ # dynamic_axes={"text": {0: "batch_size"}},
)
diff --git a/machine-learning/export/models/optimize.py b/machine-learning/export/models/optimize.py
index b0ef1ee60a..48b0c67634 100644
--- a/machine-learning/export/models/optimize.py
+++ b/machine-learning/export/models/optimize.py
@@ -5,13 +5,26 @@ import onnxruntime as ort
import onnxsim
+def save_onnx(model: onnx.ModelProto, output_path: Path | str) -> None:
+ try:
+ onnx.save(model, output_path)
+ except ValueError as e:
+ if "The proto size is larger than the 2 GB limit." in str(e):
+ onnx.save(model, output_path, save_as_external_data=True, size_threshold=1_000_000)
+ else:
+ raise e
+
+
def optimize_onnxsim(model_path: Path | str, output_path: Path | str) -> None:
model_path = Path(model_path)
output_path = Path(output_path)
model = onnx.load(model_path.as_posix())
- model, check = onnxsim.simplify(model, skip_shape_inference=True)
+ model, check = onnxsim.simplify(model)
assert check, "Simplified ONNX model could not be validated"
- onnx.save(model, output_path.as_posix())
+ for file in model_path.parent.iterdir():
+ if file.name.startswith("Constant") or "onnx" in file.name or file.suffix == ".weight":
+ file.unlink()
+ save_onnx(model, output_path)
def optimize_ort(
@@ -33,6 +46,4 @@ def optimize(model_path: Path | str) -> None:
model_path = Path(model_path)
optimize_ort(model_path, model_path)
- # onnxsim serializes large models as a blob, which uses much more memory when loading the model at runtime
- if not any(file.name.startswith("Constant") for file in model_path.parent.iterdir()):
- optimize_onnxsim(model_path, model_path)
+ optimize_onnxsim(model_path, model_path)
diff --git a/machine-learning/export/run.py b/machine-learning/export/run.py
index 5ce32189e2..3edb5644e3 100644
--- a/machine-learning/export/run.py
+++ b/machine-learning/export/run.py
@@ -3,74 +3,111 @@ import os
from pathlib import Path
from tempfile import TemporaryDirectory
-from huggingface_hub import create_repo, login, upload_folder
+import torch
+from huggingface_hub import create_repo, upload_folder
from models import mclip, openclip
+from models.optimize import optimize
from rich.progress import Progress
models = [
- "RN50::openai",
- "RN50::yfcc15m",
- "RN50::cc12m",
+ "M-CLIP/LABSE-Vit-L-14",
+ "M-CLIP/XLM-Roberta-Large-Vit-B-16Plus",
+ "M-CLIP/XLM-Roberta-Large-Vit-B-32",
+ "M-CLIP/XLM-Roberta-Large-Vit-L-14",
"RN101::openai",
"RN101::yfcc15m",
- "RN50x4::openai",
+ "RN50::cc12m",
+ "RN50::openai",
+ "RN50::yfcc15m",
"RN50x16::openai",
+ "RN50x4::openai",
"RN50x64::openai",
- "ViT-B-32::openai",
+ "ViT-B-16-SigLIP-256::webli",
+ "ViT-B-16-SigLIP-384::webli",
+ "ViT-B-16-SigLIP-512::webli",
+ "ViT-B-16-SigLIP-i18n-256::webli",
+ "ViT-B-16-SigLIP::webli",
+ "ViT-B-16-plus-240::laion400m_e31",
+ "ViT-B-16-plus-240::laion400m_e32",
+ "ViT-B-16::laion400m_e31",
+ "ViT-B-16::laion400m_e32",
+ "ViT-B-16::openai",
+ "ViT-B-32::laion2b-s34b-b79k",
"ViT-B-32::laion2b_e16",
"ViT-B-32::laion400m_e31",
"ViT-B-32::laion400m_e32",
- "ViT-B-32::laion2b-s34b-b79k",
- "ViT-B-16::openai",
- "ViT-B-16::laion400m_e31",
- "ViT-B-16::laion400m_e32",
- "ViT-B-16-plus-240::laion400m_e31",
- "ViT-B-16-plus-240::laion400m_e32",
- "ViT-L-14::openai",
+ "ViT-B-32::openai",
+ "ViT-H-14-378-quickgelu::dfn5b",
+ "ViT-H-14-quickgelu::dfn5b",
+ "ViT-H-14::laion2b-s32b-b79k",
+ "ViT-L-14-336::openai",
+ "ViT-L-14-quickgelu::dfn2b",
+ "ViT-L-14::laion2b-s32b-b82k",
"ViT-L-14::laion400m_e31",
"ViT-L-14::laion400m_e32",
- "ViT-L-14::laion2b-s32b-b82k",
- "ViT-L-14-336::openai",
- "ViT-H-14::laion2b-s32b-b79k",
+ "ViT-L-14::openai",
+ "ViT-L-16-SigLIP-256::webli",
+ "ViT-L-16-SigLIP-384::webli",
+ "ViT-SO400M-14-SigLIP-384::webli",
"ViT-g-14::laion2b-s12b-b42k",
- "M-CLIP/LABSE-Vit-L-14",
- "M-CLIP/XLM-Roberta-Large-Vit-B-32",
- "M-CLIP/XLM-Roberta-Large-Vit-B-16Plus",
- "M-CLIP/XLM-Roberta-Large-Vit-L-14",
+ "nllb-clip-base-siglip::mrl",
+ "nllb-clip-base-siglip::v1",
+ "nllb-clip-large-siglip::mrl",
+ "nllb-clip-large-siglip::v1",
+ "xlm-roberta-base-ViT-B-32::laion5b_s13b_b90k",
+ "xlm-roberta-large-ViT-H-14::frozen_laion5b_s13b_b90k",
]
-login(token=os.environ["HF_AUTH_TOKEN"])
+# glob to delete old UUID blobs when reuploading models
+uuid_char = "[a-fA-F0-9]"
+uuid_glob = uuid_char * 8 + "-" + uuid_char * 4 + "-" + uuid_char * 4 + "-" + uuid_char * 4 + "-" + uuid_char * 12
+
+# remote repo files to be deleted before uploading
+# deletion is in the same commit as the upload, so it's atomic
+delete_patterns = ["**/*onnx*", "**/Constant*", "**/*.weight", "**/*.bias", f"**/{uuid_glob}"]
with Progress() as progress:
- task1 = progress.add_task("[green]Exporting models...", total=len(models))
- task2 = progress.add_task("[yellow]Uploading models...", total=len(models))
-
+ task = progress.add_task("[green]Exporting models...", total=len(models))
+ token = os.environ.get("HF_AUTH_TOKEN")
+ torch.backends.mha.set_fastpath_enabled(False)
with TemporaryDirectory() as tmp:
tmpdir = Path(tmp)
for model in models:
model_name = model.split("/")[-1].replace("::", "__")
+ hf_model_name = model_name.replace("xlm-roberta-large", "XLM-Roberta-Large")
+ hf_model_name = model_name.replace("xlm-roberta-base", "XLM-Roberta-Base")
config_path = tmpdir / model_name / "config.json"
- def upload() -> None:
- progress.update(task2, description=f"[yellow]Uploading {model_name}")
- repo_id = f"immich-app/{model_name}"
-
- create_repo(repo_id, exist_ok=True)
- upload_folder(repo_id=repo_id, folder_path=tmpdir / model_name)
- progress.update(task2, advance=1)
-
def export() -> None:
- progress.update(task1, description=f"[green]Exporting {model_name}")
- visual_dir = tmpdir / model_name / "visual"
- textual_dir = tmpdir / model_name / "textual"
+ progress.update(task, description=f"[green]Exporting {hf_model_name}")
+ visual_dir = tmpdir / hf_model_name / "visual"
+ textual_dir = tmpdir / hf_model_name / "textual"
if model.startswith("M-CLIP"):
- mclip.to_onnx(model, visual_dir, textual_dir)
+ visual_path, textual_path = mclip.to_onnx(model, visual_dir, textual_dir)
else:
name, _, pretrained = model_name.partition("__")
- openclip.to_onnx(openclip.OpenCLIPModelConfig(name, pretrained), visual_dir, textual_dir)
+ config = openclip.OpenCLIPModelConfig(name, pretrained)
+ visual_path, textual_path = openclip.to_onnx(config, visual_dir, textual_dir)
+ progress.update(task, description=f"[green]Optimizing {hf_model_name} (visual)")
+ optimize(visual_path)
+ progress.update(task, description=f"[green]Optimizing {hf_model_name} (textual)")
+ optimize(textual_path)
- progress.update(task1, advance=1)
gc.collect()
+ def upload() -> None:
+ progress.update(task, description=f"[yellow]Uploading {hf_model_name}")
+ repo_id = f"immich-app/{hf_model_name}"
+
+ create_repo(repo_id, exist_ok=True)
+ upload_folder(
+ repo_id=repo_id,
+ folder_path=tmpdir / hf_model_name,
+ delete_patterns=delete_patterns,
+ token=token,
+ )
+
export()
- upload()
+ if token is not None:
+ upload()
+ progress.update(task, advance=1)
diff --git a/server/src/constants.ts b/server/src/constants.ts
index 0d1d992992..422fa21a1b 100644
--- a/server/src/constants.ts
+++ b/server/src/constants.ts
@@ -93,39 +93,50 @@ export const supportedPresetTokens = [
type ModelInfo = { dimSize: number };
export const CLIP_MODEL_INFO: Record<string, ModelInfo> = {
- RN50__openai: { dimSize: 1024 },
- RN50__yfcc15m: { dimSize: 1024 },
- RN50__cc12m: { dimSize: 1024 },
RN101__openai: { dimSize: 512 },
RN101__yfcc15m: { dimSize: 512 },
- RN50x4__openai: { dimSize: 640 },
- RN50x16__openai: { dimSize: 768 },
- RN50x64__openai: { dimSize: 1024 },
- 'ViT-B-32__openai': { dimSize: 512 },
+ 'ViT-B-16__laion400m_e31': { dimSize: 512 },
+ 'ViT-B-16__laion400m_e32': { dimSize: 512 },
+ 'ViT-B-16__openai': { dimSize: 512 },
+ 'ViT-B-32__laion2b-s34b-b79k': { dimSize: 512 },
'ViT-B-32__laion2b_e16': { dimSize: 512 },
'ViT-B-32__laion400m_e31': { dimSize: 512 },
'ViT-B-32__laion400m_e32': { dimSize: 512 },
- 'ViT-B-32__laion2b-s34b-b79k': { dimSize: 512 },
- 'ViT-B-16__openai': { dimSize: 512 },
- 'ViT-B-16__laion400m_e31': { dimSize: 512 },
- 'ViT-B-16__laion400m_e32': { dimSize: 512 },
+ 'ViT-B-32__openai': { dimSize: 512 },
+ 'XLM-Roberta-Base-ViT-B-32__laion5b_s13b_b90k': { dimSize: 512 },
+ 'XLM-Roberta-Large-Vit-B-32': { dimSize: 512 },
+ RN50x4__openai: { dimSize: 640 },
'ViT-B-16-plus-240__laion400m_e31': { dimSize: 640 },
'ViT-B-16-plus-240__laion400m_e32': { dimSize: 640 },
- 'ViT-L-14__openai': { dimSize: 768 },
- 'ViT-L-14__laion400m_e31': { dimSize: 768 },
- 'ViT-L-14__laion400m_e32': { dimSize: 768 },
- 'ViT-L-14__laion2b-s32b-b82k': { dimSize: 768 },
+ 'XLM-Roberta-Large-Vit-B-16Plus': { dimSize: 640 },
+ 'LABSE-Vit-L-14': { dimSize: 768 },
+ RN50x16__openai: { dimSize: 768 },
+ 'ViT-B-16-SigLIP-256__webli': { dimSize: 768 },
+ 'ViT-B-16-SigLIP-384__webli': { dimSize: 768 },
+ 'ViT-B-16-SigLIP-512__webli': { dimSize: 768 },
+ 'ViT-B-16-SigLIP-i18n-256__webli': { dimSize: 768 },
+ 'ViT-B-16-SigLIP__webli': { dimSize: 768 },
'ViT-L-14-336__openai': { dimSize: 768 },
'ViT-L-14-quickgelu__dfn2b': { dimSize: 768 },
- 'ViT-H-14__laion2b-s32b-b79k': { dimSize: 1024 },
- 'ViT-H-14-quickgelu__dfn5b': { dimSize: 1024 },
- 'ViT-H-14-378-quickgelu__dfn5b': { dimSize: 1024 },
- 'ViT-g-14__laion2b-s12b-b42k': { dimSize: 1024 },
- 'LABSE-Vit-L-14': { dimSize: 768 },
- 'XLM-Roberta-Large-Vit-B-32': { dimSize: 512 },
- 'XLM-Roberta-Large-Vit-B-16Plus': { dimSize: 640 },
+ 'ViT-L-14__laion2b-s32b-b82k': { dimSize: 768 },
+ 'ViT-L-14__laion400m_e31': { dimSize: 768 },
+ 'ViT-L-14__laion400m_e32': { dimSize: 768 },
+ 'ViT-L-14__openai': { dimSize: 768 },
'XLM-Roberta-Large-Vit-L-14': { dimSize: 768 },
- 'XLM-Roberta-Large-ViT-H-14__frozen_laion5b_s13b_b90k': { dimSize: 1024 },
+ 'nllb-clip-base-siglip__mrl': { dimSize: 768 },
'nllb-clip-base-siglip__v1': { dimSize: 768 },
+ RN50__cc12m: { dimSize: 1024 },
+ RN50__openai: { dimSize: 1024 },
+ RN50__yfcc15m: { dimSize: 1024 },
+ RN50x64__openai: { dimSize: 1024 },
+ 'ViT-H-14-378-quickgelu__dfn5b': { dimSize: 1024 },
+ 'ViT-H-14-quickgelu__dfn5b': { dimSize: 1024 },
+ 'ViT-H-14__laion2b-s32b-b79k': { dimSize: 1024 },
+ 'ViT-L-16-SigLIP-256__webli': { dimSize: 1024 },
+ 'ViT-L-16-SigLIP-384__webli': { dimSize: 1024 },
+ 'ViT-g-14__laion2b-s12b-b42k': { dimSize: 1024 },
+ 'XLM-Roberta-Large-ViT-H-14__frozen_laion5b_s13b_b90k': { dimSize: 1024 },
+ 'ViT-SO400M-14-SigLIP-384__webli': { dimSize: 1152 },
+ 'nllb-clip-large-siglip__mrl': { dimSize: 1152 },
'nllb-clip-large-siglip__v1': { dimSize: 1152 },
};