FROM mambaorg/micromamba:1.5.10-noble
ENV CONDA_OVERRIDE_CUDA=12
COPY --chown=$MAMBA_USER:$MAMBA_USER conda.yml /tmp/conda.yml
RUN micromamba install -y -n base -f /tmp/conda.yml \
&& micromamba install -y -n base conda-forge::procps-ng \
&& micromamba env export --name base --explicit > environment.lock \
&& echo ">> CONDA_LOCK_START" \
&& cat environment.lock \
&& echo "<< CONDA_LOCK_END" \
&& micromamba clean -a -y
USER root
ENV PATH="$MAMBA_ROOT_PREFIX/bin:$PATH"
#1 [internal] load build definition from Containerfile
#1 transferring dockerfile: 542B 0.0s done
#1 DONE 0.0s
#2 [internal] load metadata for docker.io/mambaorg/micromamba:1.5.10-noble
#2 ...
#3 [auth] mambaorg/micromamba:pull token for registry-1.docker.io
#3 DONE 0.0s
#2 [internal] load metadata for docker.io/mambaorg/micromamba:1.5.10-noble
#2 DONE 1.1s
#4 [internal] load .dockerignore
#4 transferring context: 2B done
#4 DONE 0.0s
#5 [internal] load build context
#5 DONE 0.0s
#6 [1/3] FROM docker.io/mambaorg/micromamba:1.5.10-noble@sha256:a0a4da2d5315f0d5b9d98196f2e9ecf50152c750bed4023bb127baade7e8faca
#6 resolve docker.io/mambaorg/micromamba:1.5.10-noble@sha256:a0a4da2d5315f0d5b9d98196f2e9ecf50152c750bed4023bb127baade7e8faca 0.0s done
#6 DONE 0.0s
#7 [auth] sharing credentials for 195996028523.dkr.ecr.eu-west-1.amazonaws.com
#7 DONE 0.0s
#8 importing cache manifest from 195996028523.dkr.ecr.eu-west-1.amazonaws.com/wave/build/cache:8410848e83d3b19e
#8 ERROR: failed to configure registry cache importer: 195996028523.dkr.ecr.eu-west-1.amazonaws.com/wave/build/cache:8410848e83d3b19e: not found
#5 [internal] load build context
#5 transferring context: 198B 0.0s done
#5 DONE 0.1s
#6 [1/3] FROM docker.io/mambaorg/micromamba:1.5.10-noble@sha256:a0a4da2d5315f0d5b9d98196f2e9ecf50152c750bed4023bb127baade7e8faca
#6 DONE 0.3s
#6 [1/3] FROM docker.io/mambaorg/micromamba:1.5.10-noble@sha256:a0a4da2d5315f0d5b9d98196f2e9ecf50152c750bed4023bb127baade7e8faca
#6 sha256:030a47592a0a4d4536afb78188ecab3ff9fa7ee5771b2f6a5ee0d8ed139729e9 346B / 346B 0.1s done
#6 sha256:bb36d6c3110d8825cd64743566e94bb2a65c4c898a8a0cd05569cbcb5689af07 686B / 686B 0.2s done
#6 sha256:0ea1a16bbe82e9a9906f98df703f99bb84f50b7a973057784bce54a4275781b2 0B / 648B 0.2s
#6 sha256:17dc7ea432cc5ad24408dee199f29d0cdad597274cb11bd37352261849c241b2 0B / 217B 0.2s
#6 sha256:10b8c00c10a554f94856546f418480a7d9c8136644c0fb97c725046bd6fdb578 0B / 4.08kB 0.2s
#6 sha256:0ea1a16bbe82e9a9906f98df703f99bb84f50b7a973057784bce54a4275781b2 648B / 648B 0.3s done
#6 sha256:17dc7ea432cc5ad24408dee199f29d0cdad597274cb11bd37352261849c241b2 217B / 217B 0.3s done
#6 sha256:10b8c00c10a554f94856546f418480a7d9c8136644c0fb97c725046bd6fdb578 4.08kB / 4.08kB 0.2s done
#6 sha256:403f74b0f85e9834f9d27943e5e2d26d191e619160f5477ad99adc52a4122764 284B / 284B 0.2s done
#6 sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1 32B / 32B 0.1s done
#6 sha256:92dc97a3ef369828f8d35d2242b165660dada3e3496ceef9ccb9ac3290e82bf9 524B / 524B 0.1s done
#6 sha256:dafa2b0c44d2cfb0be6721f079092ddf15dc8bc537fb07fe7c3264c15cb2e8e6 1.05MB / 29.75MB 0.2s
#6 sha256:dafa2b0c44d2cfb0be6721f079092ddf15dc8bc537fb07fe7c3264c15cb2e8e6 4.19MB / 29.75MB 0.3s
#6 sha256:dec6b097362e7c8d80e31302367f54d610b0e84d5c9cd5ccd300729608a54b18 126.56kB / 126.56kB 0.2s done
#6 sha256:f88da01cff0bc1129f1ae80576be8f3f715d1d3394d6ba35a93aa77f9a115733 0B / 6.20MB 0.2s
#6 sha256:dafa2b0c44d2cfb0be6721f079092ddf15dc8bc537fb07fe7c3264c15cb2e8e6 11.53MB / 29.75MB 0.5s
#6 sha256:f88da01cff0bc1129f1ae80576be8f3f715d1d3394d6ba35a93aa77f9a115733 6.20MB / 6.20MB 0.3s done
#6 sha256:dafa2b0c44d2cfb0be6721f079092ddf15dc8bc537fb07fe7c3264c15cb2e8e6 18.87MB / 29.75MB 0.6s
#6 sha256:dafa2b0c44d2cfb0be6721f079092ddf15dc8bc537fb07fe7c3264c15cb2e8e6 29.75MB / 29.75MB 0.8s
#6 sha256:dafa2b0c44d2cfb0be6721f079092ddf15dc8bc537fb07fe7c3264c15cb2e8e6 29.75MB / 29.75MB 0.8s done
#6 extracting sha256:dafa2b0c44d2cfb0be6721f079092ddf15dc8bc537fb07fe7c3264c15cb2e8e6
#6 extracting sha256:dafa2b0c44d2cfb0be6721f079092ddf15dc8bc537fb07fe7c3264c15cb2e8e6 1.1s done
#6 DONE 2.4s
#6 [1/3] FROM docker.io/mambaorg/micromamba:1.5.10-noble@sha256:a0a4da2d5315f0d5b9d98196f2e9ecf50152c750bed4023bb127baade7e8faca
#6 extracting sha256:dec6b097362e7c8d80e31302367f54d610b0e84d5c9cd5ccd300729608a54b18
#6 extracting sha256:dec6b097362e7c8d80e31302367f54d610b0e84d5c9cd5ccd300729608a54b18 0.4s done
#6 DONE 2.8s
#6 [1/3] FROM docker.io/mambaorg/micromamba:1.5.10-noble@sha256:a0a4da2d5315f0d5b9d98196f2e9ecf50152c750bed4023bb127baade7e8faca
#6 extracting sha256:f88da01cff0bc1129f1ae80576be8f3f715d1d3394d6ba35a93aa77f9a115733
#6 extracting sha256:f88da01cff0bc1129f1ae80576be8f3f715d1d3394d6ba35a93aa77f9a115733 0.5s done
#6 DONE 3.3s
#6 [1/3] FROM docker.io/mambaorg/micromamba:1.5.10-noble@sha256:a0a4da2d5315f0d5b9d98196f2e9ecf50152c750bed4023bb127baade7e8faca
#6 extracting sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1
#6 extracting sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1 0.3s done
#6 DONE 3.6s
#6 [1/3] FROM docker.io/mambaorg/micromamba:1.5.10-noble@sha256:a0a4da2d5315f0d5b9d98196f2e9ecf50152c750bed4023bb127baade7e8faca
#6 extracting sha256:92dc97a3ef369828f8d35d2242b165660dada3e3496ceef9ccb9ac3290e82bf9
#6 extracting sha256:92dc97a3ef369828f8d35d2242b165660dada3e3496ceef9ccb9ac3290e82bf9 0.5s done
#6 extracting sha256:403f74b0f85e9834f9d27943e5e2d26d191e619160f5477ad99adc52a4122764
#6 extracting sha256:403f74b0f85e9834f9d27943e5e2d26d191e619160f5477ad99adc52a4122764 0.4s done
#6 extracting sha256:10b8c00c10a554f94856546f418480a7d9c8136644c0fb97c725046bd6fdb578
#6 extracting sha256:10b8c00c10a554f94856546f418480a7d9c8136644c0fb97c725046bd6fdb578 0.4s done
#6 DONE 4.8s
#6 [1/3] FROM docker.io/mambaorg/micromamba:1.5.10-noble@sha256:a0a4da2d5315f0d5b9d98196f2e9ecf50152c750bed4023bb127baade7e8faca
#6 extracting sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1 0.5s done
#6 extracting sha256:17dc7ea432cc5ad24408dee199f29d0cdad597274cb11bd37352261849c241b2
#6 extracting sha256:17dc7ea432cc5ad24408dee199f29d0cdad597274cb11bd37352261849c241b2 0.4s done
#6 DONE 5.7s
#6 [1/3] FROM docker.io/mambaorg/micromamba:1.5.10-noble@sha256:a0a4da2d5315f0d5b9d98196f2e9ecf50152c750bed4023bb127baade7e8faca
#6 extracting sha256:bb36d6c3110d8825cd64743566e94bb2a65c4c898a8a0cd05569cbcb5689af07
#6 extracting sha256:bb36d6c3110d8825cd64743566e94bb2a65c4c898a8a0cd05569cbcb5689af07 0.4s done
#6 DONE 6.1s
#6 [1/3] FROM docker.io/mambaorg/micromamba:1.5.10-noble@sha256:a0a4da2d5315f0d5b9d98196f2e9ecf50152c750bed4023bb127baade7e8faca
#6 extracting sha256:0ea1a16bbe82e9a9906f98df703f99bb84f50b7a973057784bce54a4275781b2
#6 extracting sha256:0ea1a16bbe82e9a9906f98df703f99bb84f50b7a973057784bce54a4275781b2 0.4s done
#6 extracting sha256:030a47592a0a4d4536afb78188ecab3ff9fa7ee5771b2f6a5ee0d8ed139729e9
#6 extracting sha256:030a47592a0a4d4536afb78188ecab3ff9fa7ee5771b2f6a5ee0d8ed139729e9 0.4s done
#6 DONE 6.9s
#9 [2/3] COPY --chown=mambauser:mambauser conda.yml /tmp/conda.yml
#9 DONE 0.8s
#10 [3/3] RUN micromamba install -y -n base -f /tmp/conda.yml && micromamba install -y -n base conda-forge::procps-ng && micromamba env export --name base --explicit > environment.lock && echo ">> CONDA_LOCK_START" && cat environment.lock && echo "<< CONDA_LOCK_END" && micromamba clean -a -y
#10 37.01
#10 37.01 Transaction
#10 37.01
#10 37.01 Prefix: /opt/conda
#10 37.01
#10 37.01 Updating specs:
#10 37.01
#10 37.01 - pytorch
#10 37.01 - torchvision
#10 37.01 - torchaudio
#10 37.01 - pytorch-cuda=12.4
#10 37.01 - jaxlib=*[build=cuda12*]
#10 37.01 - scvi-tools=1.2.2
#10 37.01
#10 37.01
#10 37.03 Package Version Build Channel Size
#10 37.03 ────────────────────────────────────────────────────────────────────────────────────────────────────
#10 37.03 Install:
#10 37.03 ────────────────────────────────────────────────────────────────────────────────────────────────────
#10 37.03
#10 37.03 + pytorch-mutex 1.0 cuda pytorch 3kB
#10 37.03 + _libgcc_mutex 0.1 conda_forge conda-forge 3kB
#10 37.03 + python_abi 3.12 5_cp312 conda-forge 6kB
#10 37.03 + ld_impl_linux-64 2.43 h712a8e2_2 conda-forge 669kB
#10 37.03 + ca-certificates 2024.12.14 hbcca054_0 conda-forge 157kB
#10 37.03 + libgomp 14.2.0 h77fa898_1 conda-forge 461kB
#10 37.03 + libgcc 14.2.0 h77fa898_1 conda-forge 849kB
#10 37.03 + libgcc-ng 14.2.0 h69a702a_1 conda-forge 54kB
#10 37.03 + libzlib 1.2.13 h4ab18f5_6 conda-forge 62kB
#10 37.03 + llvm-openmp 15.0.7 h0cdce71_0 conda-forge 3MB
#10 37.03 + _openmp_mutex 4.5 2_kmp_llvm conda-forge 6kB
#10 37.03 + libev 4.33 hd590300_2 conda-forge 113kB
#10 37.03 + libiconv 1.17 hd590300_2 conda-forge 706kB
#10 37.03 + lame 3.100 h166bdaf_1003 conda-forge 508kB
#10 37.03 + nettle 3.6 he412f7d_0 conda-forge 7MB
#10 37.03 + zlib 1.2.13 h4ab18f5_6 conda-forge 93kB
#10 37.03 + libbrotlicommon 1.1.0 hb9d3cd8_2 conda-forge 69kB
#10 37.03 + rav1e 0.6.6 he8a937b_2 conda-forge 15MB
#10 37.03 + c-ares 1.34.4 hb9d3cd8_0 conda-forge 206kB
#10 37.03 + libdeflate 1.20 hd590300_0 conda-forge 72kB
#10 37.03 + xorg-libxdmcp 1.1.5 hb9d3cd8_0 conda-forge 20kB
#10 37.03 + xorg-libxau 1.0.12 hb9d3cd8_0 conda-forge 15kB
#10 37.03 + pthread-stubs 0.4 hb9d3cd8_1002 conda-forge 8kB
#10 37.03 + tk 8.6.13 noxft_h4845f30_101 conda-forge 3MB
#10 37.03 + libxcrypt 4.4.36 hd590300_1 conda-forge 100kB
#10 37.03 + libsqlite 3.46.0 hde9e2c9_0 conda-forge 865kB
#10 37.03 + libexpat 2.6.4 h5888daf_0 conda-forge 73kB
#10 37.03 + libffi 3.4.2 h7f98852_5 conda-forge 58kB
#10 37.03 + yaml 0.2.5 h7f98852_2 conda-forge 89kB
#10 37.03 + ncurses 6.5 he02047a_1 conda-forge 889kB
#10 37.03 + libgfortran5 14.2.0 hd5240d6_1 conda-forge 1MB
#10 37.03 + openssl 3.4.0 h7b32b05_1 conda-forge 3MB
#10 37.03 + giflib 5.2.2 hd590300_0 conda-forge 77kB
#10 37.03 + libwebp-base 1.4.0 hd590300_0 conda-forge 439kB
#10 37.03 + libjpeg-turbo 3.0.0 hd590300_1 conda-forge 619kB
#10 37.03 + keyutils 1.6.1 h166bdaf_0 conda-forge 118kB
#10 37.03 + dav1d 1.2.1 hd590300_0 conda-forge 760kB
#10 37.03 + liblzma 5.6.3 hb9d3cd8_1 conda-forge 111kB
#10 37.03 + libstdcxx 14.2.0 hc0a3c3a_1 conda-forge 4MB
#10 37.03 + bzip2 1.0.8 h4bc722e_7 conda-forge 253kB
#10 37.03 + libpng 1.6.43 h2797004_0 conda-forge 288kB
#10 37.03 + libuuid 2.38.1 h0b41bf4_0 conda-forge 34kB
#10 37.03 + libnsl 2.0.1 hd590300_0 conda-forge 33kB
#10 37.03 + libbrotlienc 1.1.0 hb9d3cd8_2 conda-forge 282kB
#10 37.03 + libbrotlidec 1.1.0 hb9d3cd8_2 conda-forge 33kB
#10 37.03 + libxcb 1.15 h0b41bf4_0 conda-forge 384kB
#10 37.03 + libedit 3.1.20240808 pl5321h7949ede_0 conda-forge 135kB
#10 37.03 + readline 8.2 h8228510_1 conda-forge 281kB
#10 37.03 + libgfortran 14.2.0 h69a702a_1 conda-forge 54kB
#10 37.03 + libssh2 1.11.0 h0841786_0 conda-forge 271kB
#10 37.03 + xz-tools 5.6.3 hb9d3cd8_1 conda-forge 90kB
#10 37.03 + xz-gpl-tools 5.6.3 hbcc6ac9_1 conda-forge 33kB
#10 37.03 + liblzma-devel 5.6.3 hb9d3cd8_1 conda-forge 377kB
#10 37.03 + libsanitizer 12.4.0 h46f95d5_1 conda-forge 4MB
#10 37.03 + snappy 1.2.1 h8bd8927_1 conda-forge 43kB
#10 37.03 + svt-av1 2.3.0 h5888daf_0 conda-forge 3MB
#10 37.03 + libstdcxx-ng 14.2.0 h4852527_1 conda-forge 54kB
#10 37.03 + freetype 2.12.1 h267a509_2 conda-forge 635kB
#10 37.03 + brotli-bin 1.1.0 hb9d3cd8_2 conda-forge 19kB
#10 37.03 + libgfortran-ng 14.2.0 h69a702a_1 conda-forge 54kB
#10 37.03 + xz 5.6.3 hbcc6ac9_1 conda-forge 23kB
#10 37.03 + openh264 2.1.1 h780b84a_0 conda-forge 2MB
#10 37.03 + icu 73.2 h59595ed_0 conda-forge 12MB
#10 37.03 + libllvm14 14.0.6 hcd5def8_4 conda-forge 31MB
#10 37.03 + gnutls 3.6.13 h85f3911_1 conda-forge 2MB
#10 37.03 + gmp 6.3.0 hac33072_2 conda-forge 460kB
#10 37.03 + lz4-c 1.9.4 hcb278e6_0 conda-forge 143kB
#10 37.03 + libaec 1.1.3 h59595ed_0 conda-forge 35kB
#10 37.03 + libnghttp2 1.58.0 h47da74e_1 conda-forge 632kB
#10 37.03 + libabseil 20240116.2 cxx17_he02047a_1 conda-forge 1MB
#10 37.03 + lerc 4.0.0 h27087fc_0 conda-forge 282kB
#10 37.03 + qhull 2020.2 h434a139_5 conda-forge 553kB
#10 37.03 + zstd 1.5.6 ha6fb4c9_0 conda-forge 555kB
#10 37.03 + krb5 1.21.3 h659f571_0 conda-forge 1MB
#10 37.03 + aom 3.9.1 hac33072_0 conda-forge 3MB
#10 37.03 + brotli 1.1.0 hb9d3cd8_2 conda-forge 19kB
#10 37.03 + libxml2 2.12.7 hc051c1a_1 conda-forge 705kB
#10 37.03 + mpfr 4.2.1 h90cbb55_3 conda-forge 635kB
#10 37.03 + libre2-11 2023.09.01 h5a48ba9_2 conda-forge 233kB
#10 37.03 + libprotobuf 4.25.3 h08a7969_0 conda-forge 3MB
#10 37.03 + libtiff 4.6.0 h1dd3fc0_3 conda-forge 283kB
#10 37.03 + blosc 1.21.5 hc2324a3_1 conda-forge 49kB
#10 37.03 + libcurl 8.8.0 hca28451_1 conda-forge 410kB
#10 37.03 + libavif16 1.1.1 h1909e37_2 conda-forge 116kB
#10 37.03 + libhwloc 2.11.2 default_he43201b_1000 conda-forge 2MB
#10 37.03 + mpc 1.3.1 h24ddda3_1 conda-forge 117kB
#10 37.03 + re2 2023.09.01 h7f4b329_2 conda-forge 27kB
#10 37.03 + openjpeg 2.5.2 h488ebb8_0 conda-forge 342kB
#10 37.03 + lcms2 2.16 hb7c19ff_0 conda-forge 245kB
#10 37.03 + libwebp 1.4.0 h2c329e2_0 conda-forge 92kB
#10 37.03 + hdf5 1.14.3 nompi_hdf9ad27_105 conda-forge 4MB
#10 37.03 + tbb 2021.13.0 hceb3a55_1 conda-forge 176kB
#10 37.03 + libgrpc 1.62.2 h15f2491_0 conda-forge 7MB
#10 37.03 + mkl 2022.2.1 h84fe81f_16997 conda-forge 165MB
#10 37.03 + blas 1.0 mkl conda-forge 1kB
#10 37.03 + libblas 3.9.0 16_linux64_mkl conda-forge 13kB
#10 37.03 + libcblas 3.9.0 16_linux64_mkl conda-forge 13kB
#10 37.03 + liblapack 3.9.0 16_linux64_mkl conda-forge 13kB
#10 37.03 + pybind11-abi 4 hd8ed1ab_3 conda-forge 10kB
#10 37.03 + tzdata 2024b hc8b5060_0 conda-forge 122kB
#10 37.03 + libstdcxx-devel_linux-64 12.4.0 ha4f9413_101 conda-forge 12MB
#10 37.03 + libgcc-devel_linux-64 12.4.0 ha4f9413_101 conda-forge 3MB
#10 37.03 + kernel-headers_linux-64 3.10.0 he073ed8_18 conda-forge 943kB
#10 37.03 + sysroot_linux-64 2.17 h0157908_18 conda-forge 15MB
#10 37.03 + cuda-cudart 12.4.127 0 nvidia 203kB
#10 37.03 + cuda-cupti 12.4.127 0 nvidia 17MB
#10 37.03 + cuda-nvtx 12.4.127 0 nvidia 59kB
#10 37.03 + libcublas 12.4.5.8 0 nvidia 324MB
#10 37.03 + libcufft 11.2.1.3 0 nvidia 200MB
#10 37.03 + libcusolver 11.6.1.9 0 nvidia 120MB
#10 37.03 + libcusparse 12.3.1.170 0 nvidia 188MB
#10 37.03 + libnvjpeg 12.3.1.117 0 nvidia 3MB
#10 37.03 + libnvjitlink 12.4.127 0 nvidia 19MB
#10 37.03 + libnpp 12.2.5.30 0 nvidia 150MB
#10 37.03 + cuda-nvrtc 12.4.127 0 nvidia 22MB
#10 37.03 + cuda-version 12.6 3 nvidia 17kB
#10 37.03 + cuda-cudart_linux-64 12.6.77 0 nvidia 183kB
#10 37.03 + cuda-cudart-static_linux-64 12.6.77 0 nvidia 757kB
#10 37.03 + cuda-cccl_linux-64 12.6.77 0 nvidia 1MB
#10 37.03 + cuda-driver-dev_linux-64 12.6.77 0 nvidia 31kB
#10 37.03 + cuda-nvvm-dev_linux-64 12.6.20 0 nvidia 17kB
#10 37.03 + cuda-crt-dev_linux-64 12.6.20 0 nvidia 81kB
#10 37.03 + cuda-cudart-dev_linux-64 12.6.77 0 nvidia 361kB
#10 37.03 + cuda-nvcc-dev_linux-64 12.6.20 0 nvidia 14MB
#10 37.03 + ffmpeg 4.3 hf484d3e_0 pytorch 10MB
#10 37.03 + python 3.12.3 hab00c5b_0_cpython conda-forge 32MB
#10 37.03 + binutils_impl_linux-64 2.43 h4bf12b8_2 conda-forge 6MB
#10 37.03 + nccl 2.24.3.1 hb92ee24_0 conda-forge 126MB
#10 37.03 + cudnn 8.9.7.29 h092f7fd_3 conda-forge 468MB
#10 37.03 + gcc_impl_linux-64 12.4.0 hb2e57f8_1 conda-forge 62MB
#10 37.03 + binutils_linux-64 2.43 h4852527_2 conda-forge 35kB
#10 37.03 + gxx_impl_linux-64 12.4.0 h613a52c_1 conda-forge 13MB
#10 37.03 + gcc_linux-64 12.4.0 h6b7512a_7 conda-forge 32kB
#10 37.03 + gxx_linux-64 12.4.0 h8489865_7 conda-forge 30kB
#10 37.03 + libnvfatbin 12.6.77 0 nvidia 802kB
#10 37.03 + libcufile 1.11.1.6 0 nvidia 921kB
#10 37.03 + cuda-opencl 12.6.77 0 nvidia 26kB
#10 37.03 + cuda-nvvm-tools 12.6.20 0 nvidia 13MB
#10 37.03 + cuda-crt-tools 12.6.20 0 nvidia 19kB
#10 37.03 + cuda-nvvm-impl 12.6.20 0 nvidia 9MB
#10 37.03 + libcurand 10.3.7.77 0 nvidia 42MB
#10 37.03 + cuda-cccl 12.6.77 0 nvidia 17kB
#10 37.03 + cuda-nvcc-tools 12.6.20 0 nvidia 28MB
#10 37.03 + cuda-libraries 12.4.1 0 nvidia 2kB
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#10 37.03 + cuda-runtime 12.4.1 0 nvidia 2kB
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#10 37.03 + cuda-nvcc_linux-64 12.6.20 0 nvidia 20kB
#10 37.03 + cuda-nvcc 12.6.20 0 nvidia 17kB
#10 37.03 + wheel 0.45.1 pyhd8ed1ab_1 conda-forge 63kB
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#10 37.03 + etils 1.10.0 pyhd8ed1ab_1 conda-forge 784kB
#10 37.03 + humanize 4.11.0 pyhd8ed1ab_1 conda-forge 66kB
#10 37.03 + charset-normalizer 3.4.1 pyhd8ed1ab_0 conda-forge 47kB
#10 37.03 + idna 3.10 pyhd8ed1ab_1 conda-forge 50kB
#10 37.03 + certifi 2024.12.14 pyhd8ed1ab_0 conda-forge 162kB
#10 37.03 + mpmath 1.3.0 pyhd8ed1ab_1 conda-forge 440kB
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#10 37.03 + munkres 1.1.4 pyh9f0ad1d_0 conda-forge 12kB
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#10 37.03 + pytz 2024.1 pyhd8ed1ab_0 conda-forge 189kB
#10 37.03 + python-tzdata 2024.2 pyhd8ed1ab_1 conda-forge 142kB
#10 37.03 + threadpoolctl 3.5.0 pyhc1e730c_0 conda-forge 24kB
#10 37.03 + joblib 1.4.2 pyhd8ed1ab_1 conda-forge 220kB
#10 37.03 + array-api-compat 1.10.0 pyhd8ed1ab_0 conda-forge 38kB
#10 37.03 + exceptiongroup 1.2.2 pyhd8ed1ab_1 conda-forge 20kB
#10 37.03 + natsort 8.4.0 pyh29332c3_1 conda-forge 39kB
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#10 37.03 + zipp 3.21.0 pyhd8ed1ab_1 conda-forge 22kB
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#10 37.03 + opt_einsum 3.4.0 pyhd8ed1ab_1 conda-forge 62kB
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#10 37.03 + importlib-metadata 8.5.0 pyha770c72_1 conda-forge 29kB
#10 37.03 + markdown-it-py 3.0.0 pyhd8ed1ab_1 conda-forge 64kB
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#10 37.03 + docrep 0.3.2 pyh44b312d_0 conda-forge 19kB
#10 37.03 + opt-einsum 3.4.0 hd8ed1ab_1 conda-forge 7kB
#10 37.03 + lightning-utilities 0.11.9 pyhd8ed1ab_1 conda-forge 29kB
#10 37.03 + typing-extensions 4.12.2 hd8ed1ab_1 conda-forge 10kB
#10 37.03 + markdown 3.6 pyhd8ed1ab_0 conda-forge 78kB
#10 37.03 + importlib_metadata 8.5.0 hd8ed1ab_1 conda-forge 9kB
#10 37.03 + rich 13.9.4 pyhd8ed1ab_1 conda-forge 186kB
#10 37.03 + pytorch-cuda 12.4 hc786d27_7 pytorch 7kB
#10 37.03 + markupsafe 3.0.2 py312h178313f_1 conda-forge 25kB
#10 37.03 + brotli-python 1.1.0 py312h2ec8cdc_2 conda-forge 350kB
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#10 37.03 + tensorboard-data-server 0.7.0 py312hda17c39_2 conda-forge 4MB
#10 37.03 + protobuf 4.25.3 py312h83439f5_1 conda-forge 391kB
#10 37.03 + unicodedata2 15.1.0 py312h66e93f0_1 conda-forge 369kB
#10 37.03 + pillow 10.3.0 py312hdcec9eb_0 conda-forge 42MB
#10 37.03 + kiwisolver 1.4.7 py312h68727a3_0 conda-forge 71kB
#10 37.03 + msgpack-python 1.1.0 py312h68727a3_0 conda-forge 105kB
#10 37.03 + pyyaml 6.0.2 py312h66e93f0_1 conda-forge 207kB
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#10 37.03 + numpy 1.26.4 py312heda63a1_0 conda-forge 7MB
#10 37.03 + cffi 1.17.1 py312h06ac9bb_0 conda-forge 294kB
#10 37.03 + openpyxl 3.1.5 py312h710cb58_1 conda-forge 696kB
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#10 37.03 + numba 0.59.1 py312hacefee8_0 conda-forge 6MB
#10 37.03 + contourpy 1.3.1 py312h68727a3_0 conda-forge 276kB
#10 37.03 + ml_dtypes 0.5.0 py312hf9745cd_0 conda-forge 290kB
#10 37.03 + pandas 2.2.3 py312hf9745cd_1 conda-forge 15MB
#10 37.03 + h5py 3.12.1 nompi_py312hedeef09_103 conda-forge 1MB
#10 37.03 + scipy 1.15.0 py312h180e4f1_1 conda-forge 19MB
#10 37.03 + zstandard 0.23.0 py312hef9b889_1 conda-forge 420kB
#10 37.03 + matplotlib-base 3.10.0 py312hd3ec401_0 conda-forge 8MB
#10 37.03 + tensorstore 0.1.60 py312h80f44a3_0 conda-forge 8MB
#10 37.03 + scikit-learn 1.6.0 py312h7a48858_0 conda-forge 11MB
#10 37.03 + jaxlib 0.4.23 cuda120py312h6027bbc_202 conda-forge 87MB
#10 37.03 + werkzeug 3.1.3 pyhd8ed1ab_1 conda-forge 244kB
#10 37.03 + jinja2 3.1.5 pyhd8ed1ab_0 conda-forge 113kB
#10 37.03 + sympy 1.13.3 pypyh2585a3b_103 conda-forge 5MB
#10 37.03 + ml-collections 1.0.0 pyh29332c3_0 conda-forge 62kB
#10 37.03 + xarray 2025.1.0 pyhd8ed1ab_0 conda-forge 832kB
#10 37.03 + sparse 0.15.4 pyh267e887_1 conda-forge 98kB
#10 37.03 + anndata 0.11.2 pyhd8ed1ab_0 conda-forge 113kB
#10 37.03 + urllib3 2.3.0 pyhd8ed1ab_0 conda-forge 100kB
#10 37.03 + jax 0.4.27 pyhd8ed1ab_0 conda-forge 1MB
#10 37.03 + tensorboard 2.18.0 pyhd8ed1ab_1 conda-forge 5MB
#10 37.03 + mudata 0.3.1 pyhd8ed1ab_1 conda-forge 41kB
#10 37.03 + requests 2.32.3 pyhd8ed1ab_1 conda-forge 59kB
#10 37.03 + orbax-checkpoint 0.6.4 pyhd8ed1ab_1 conda-forge 165kB
#10 37.03 + numpyro 0.16.1 pyhd8ed1ab_1 conda-forge 257kB
#10 37.03 + chex 0.1.86 pyhd8ed1ab_0 conda-forge 78kB
#10 37.03 + optax 0.2.2 pyhd8ed1ab_1 conda-forge 145kB
#10 37.03 + flax 0.10.2 pyhd8ed1ab_0 conda-forge 270kB
#10 37.03 + pytorch 2.5.1 py3.12_cuda12.4_cudnn9.1.0_0 pytorch 2GB
#10 37.03 + torchtriton 3.1.0 py312 pytorch 245MB
#10 37.03 + torchaudio 2.5.1 py312_cu124 pytorch 7MB
#10 37.03 + torchvision 0.20.1 py312_cu124 pytorch 9MB
#10 37.03 + torchmetrics 1.6.1 pyhd8ed1ab_0 conda-forge 371kB
#10 37.03 + pyro-ppl 1.9.1 pyhd8ed1ab_1 conda-forge 464kB
#10 37.03 + pytorch-lightning 2.5.0.post0 pyh101cb37_0 conda-forge 447kB
#10 37.03 + lightning 2.5.0.post0 pyhd8ed1ab_0 conda-forge 449kB
#10 37.03 + scvi-tools 1.2.2.post1 pyhd8ed1ab_1 conda-forge 270kB
#10 37.03
#10 37.03 Summary:
#10 37.03
#10 37.03 Install: 258 packages
#10 37.03
#10 37.03 Total download: 4GB
#10 37.03
#10 37.03 ────────────────────────────────────────────────────────────────────────────────────────────────────
#10 37.03
#10 37.03
#10 37.03
#10 37.03 Transaction starting
#10 349.0 By downloading and using the cuDNN conda packages, you accept the terms and conditions of the NVIDIA cuDNN EULA -
#10 349.0 https://docs.nvidia.com/deeplearning/cudnn/sla/index.html
#10 349.0
#10 351.6 warning libmamba [docrep-0.3.2-pyh44b312d_0] The following files were already present in the environment:
#10 351.6 - LICENSE
#10 366.0
#10 366.0 Transaction finished
#10 366.0
#10 366.0 To activate this environment, use:
#10 366.0
#10 366.0 micromamba activate base
#10 366.0
#10 366.0 Or to execute a single command in this environment, use:
#10 366.0
#10 366.0 micromamba run -n base mycommand
#10 366.0
#10 366.1 conda-forge/linux-64 Using cache
#10 366.1 conda-forge/noarch Using cache
#10 369.8
#10 369.8 Pinned packages:
#10 369.8 - python 3.12.*
#10 369.8
#10 390.6
#10 390.6 Transaction
#10 390.6
#10 390.6 Prefix: /opt/conda
#10 390.6
#10 390.6 Updating specs:
#10 390.6
#10 390.6 - conda-forge::procps-ng
#10 390.6
#10 390.6
#10 390.6 Package Version Build Channel Size
#10 390.6 ───────────────────────────────────────────────────────────
#10 390.6 Install:
#10 390.6 ───────────────────────────────────────────────────────────
#10 390.6
#10 390.6 + procps-ng 4.0.4 haa1a288_0 conda-forge 551kB
#10 390.6
#10 390.6 Summary:
#10 390.6
#10 390.6 Install: 1 packages
#10 390.6
#10 390.6 Total download: 551kB
#10 390.6
#10 390.6 ───────────────────────────────────────────────────────────
#10 390.6
#10 390.6
#10 390.6
#10 390.6 Transaction starting
#10 391.6
#10 391.6 Transaction finished
#10 391.6
#10 391.6 To activate this environment, use:
#10 391.6
#10 391.6 micromamba activate base
#10 391.6
#10 391.6 Or to execute a single command in this environment, use:
#10 391.6
#10 391.6 micromamba run -n base mycommand
#10 391.6
#10 392.2 Collect information..
#10 392.2 Cleaning index cache..
#10 392.2 Cleaning lock files..
#10 392.2 Package file Size
#10 392.2 ────────────────────────────────────────────────────────────────
#10 392.2 /opt/conda/pkgs
#10 392.2 ────────────────────────────────────────────────────────────────
#10 392.2
#10 392.2 _libgcc_mutex-0.1-conda_forge.tar.bz2 3kB
#10 392.2 _openmp_mutex-4.5-2_kmp_llvm.tar.bz2 6kB
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#10 392.2 anndata-0.11.2-pyhd8ed1ab_0.conda 113kB
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#10 392.2 contourpy-1.3.1-py312h68727a3_0.conda 276kB
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#10 392.2 cuda-nvcc-dev_linux-64-12.6.20-0.tar.bz2 14MB
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#10 392.2 cuda-nvcc_linux-64-12.6.20-0.tar.bz2 20kB
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#10 392.2 dav1d-1.2.1-hd590300_0.conda 760kB
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#10 392.2 gxx_linux-64-12.4.0-h8489865_7.conda 30kB
#10 392.2 h2-4.1.0-pyhd8ed1ab_1.conda 52kB
#10 392.2 h5py-3.12.1-nompi_py312hedeef09_103.conda 1MB
#10 392.2 hdf5-1.14.3-nompi_hdf9ad27_105.conda 4MB
#10 392.2 hpack-4.0.0-pyhd8ed1ab_1.conda 29kB
#10 392.2 humanize-4.11.0-pyhd8ed1ab_1.conda 66kB
#10 392.2 hyperframe-6.0.1-pyhd8ed1ab_1.conda 17kB
#10 392.2 icu-73.2-h59595ed_0.conda 12MB
#10 392.2 idna-3.10-pyhd8ed1ab_1.conda 50kB
#10 392.2 importlib-metadata-8.5.0-pyha770c72_1.conda 29kB
#10 392.2 importlib_metadata-8.5.0-hd8ed1ab_1.conda 9kB
#10 392.2 importlib_resources-6.5.2-pyhd8ed1ab_0.conda 34kB
#10 392.2 jax-0.4.27-pyhd8ed1ab_0.conda 1MB
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#10 392.2 lcms2-2.16-hb7c19ff_0.conda 245kB
#10 392.2 ld_impl_linux-64-2.43-h712a8e2_2.conda 669kB
#10 392.2 lerc-4.0.0-h27087fc_0.tar.bz2 282kB
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#10 392.2 libavif16-1.1.1-h1909e37_2.conda 116kB
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#10 392.2 libbrotlienc-1.1.0-hb9d3cd8_2.conda 282kB
#10 392.2 libcblas-3.9.0-16_linux64_mkl.tar.bz2 13kB
#10 392.2 libcublas-12.4.5.8-0.tar.bz2 324MB
#10 392.2 libcufft-11.2.1.3-0.tar.bz2 200MB
#10 392.2 libcufile-1.11.1.6-0.conda 921kB
#10 392.2 libcurand-10.3.7.77-0.conda 42MB
#10 392.2 libcurl-8.8.0-hca28451_1.conda 410kB
#10 392.2 libcusolver-11.6.1.9-0.tar.bz2 120MB
#10 392.2 libcusparse-12.3.1.170-0.tar.bz2 188MB
#10 392.2 libdeflate-1.20-hd590300_0.conda 72kB
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#10 392.2 libev-4.33-hd590300_2.conda 113kB
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#10 392.2 libgcc-14.2.0-h77fa898_1.conda 849kB
#10 392.2 libgcc-devel_linux-64-12.4.0-ha4f9413_101.conda 3MB
#10 392.2 libgcc-ng-14.2.0-h69a702a_1.conda 54kB
#10 392.2 libgfortran-14.2.0-h69a702a_1.conda 54kB
#10 392.2 libgfortran-ng-14.2.0-h69a702a_1.conda 54kB
#10 392.2 libgfortran5-14.2.0-hd5240d6_1.conda 1MB
#10 392.2 libgomp-14.2.0-h77fa898_1.conda 461kB
#10 392.2 libgrpc-1.62.2-h15f2491_0.conda 7MB
#10 392.2 libhwloc-2.11.2-default_he43201b_1000.conda 2MB
#10 392.2 libiconv-1.17-hd590300_2.conda 706kB
#10 392.2 libjpeg-turbo-3.0.0-hd590300_1.conda 619kB
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#10 392.2
#10 392.2 /home/mambauser/.mamba/pkgs
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#10 392.2
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#10 392.2
#10 392.2 Total size: 4GB
#10 392.2 Cleaning tarballs..
#10 392.5 Cleaning packages..
#10 DONE 392.6s
#11 exporting to image
#11 exporting layers
