Yes, will do! Does it matter for the agent if it runs in docker mode? I think not, right?

I deployed a new instance real quick and installed everything again. Conda gets found via which conda and is also listed when I try it with echo $PATH . The error still persists.

Hi BitingKangaroo95 , are you using Windows?

these are the last few lines from the console output - if it is helpful:
` Current configuration (clearml_agent v1.5.0, location: /tmp/clearml.conf):

api.version = 1.5
api.verify_certificate = true
api.default_version = 1.5
api.http.max_req_size = 15728640
api.http.retries.total = 240
api.http.retries.connect = 240
api.http.retries.read = 240
api.http.retries.redirect = 240
api.http.retries.status = 240
api.http.retries.backoff_factor = 1.0
api.http.retries.backoff_max = 120.0
api.http.wait_on_maintenance_forever = true
api.http.pool_maxsize = 512
api.http.pool_connections = 512
api.api_server = http://*****:8008
api.web_server = http://***:8080
api.files_server = http://:8081
api.credentials.access_key = **************
api.host = http://*********:8008
sdk.storage.cache.default_base_dir = /clearml_agent_cache
sdk.storage.cache.size.min_free_bytes = 10GB
sdk.storage.direct_access.0.url = file://
sdk.metrics.file_history_size = 100
sdk.metrics.matplotlib_untitled_history_size = 100
sdk.metrics.images.format = JPEG
sdk.metrics.images.quality = 87
sdk.metrics.images.subsampling = 0
sdk.metrics.tensorboard_single_series_per_graph = false
sdk.network.metrics.file_upload_threads = 4
sdk.network.metrics.file_upload_starvation_warning_sec = 120
sdk.network.iteration.max_retries_on_server_error = 5
sdk.network.iteration.retry_backoff_factor_sec = 10
sdk.aws.s3.key =
sdk.aws.s3.region =
sdk.aws.boto3.pool_connections = 512
sdk.aws.boto3.max_multipart_concurrency = 16
sdk.log.null_log_propagate = false
sdk.log.task_log_buffer_capacity = 66
sdk.log.disable_urllib3_info = true
sdk.development.task_reuse_time_window_in_hours = 72.0
sdk.development.vcs_repo_detect_async = true
sdk.development.store_uncommitted_code_diff = true
sdk.development.support_stopping = true
sdk.development.default_output_uri =
sdk.development.force_analyze_entire_repo = false
sdk.development.suppress_update_message = false
sdk.development.detect_with_pip_freeze = false
sdk.development.worker.report_period_sec = 2
sdk.development.worker.ping_period_sec = 30
sdk.development.worker.log_stdout = true
sdk.development.worker.report_global_mem_used = false
agent.worker_id = 12gb-robin:gpu0
agent.worker_name = 12gb-robin
agent.force_git_ssh_protocol = false
agent.python_binary =
agent.package_manager.type = conda
agent.package_manager.pip_version = <20.2
agent.package_manager.system_site_packages = true
agent.package_manager.force_upgrade = false
agent.package_manager.conda_channels.0 = pytorch
agent.package_manager.conda_channels.1 = conda-forge
agent.package_manager.conda_channels.2 = defaults
agent.package_manager.priority_optional_packages.0 = pygobject
agent.package_manager.torch_nightly = false
agent.package_manager.conda_env_as_base_docker = false
agent.venvs_dir = /root/.clearml/venvs-builds
agent.venvs_cache.max_entries = 10
agent.venvs_cache.free_space_threshold_gb = 2.0
agent.venvs_cache.path = ~/.clearml/venvs-cache
agent.vcs_cache.enabled = true
agent.vcs_cache.path = /root/.clearml/vcs-cache
agent.venv_update.enabled = false
agent.pip_download_cache.enabled = true
agent.pip_download_cache.path = /root/.clearml/pip-download-cache
agent.translate_ssh = true
agent.reload_config = false
agent.docker_pip_cache = /root/.clearml/pip-cache
agent.docker_apt_cache = /root/.clearml/apt-cache
agent.docker_force_pull = false
agent.default_docker.image = nvidia/cuda:11.6.0-cudnn8-runtime-ubuntu20.04
agent.default_docker.arguments.0 = --ipc=host
agent.default_docker.arguments.1 = --privileged
agent.enable_task_env = false
agent.hide_docker_command_env_vars.enabled = true
agent.hide_docker_command_env_vars.parse_embedded_urls = true
agent.abort_callback_max_timeout = 1800
agent.docker_internal_mounts.sdk_cache = /clearml_agent_cache
agent.docker_internal_mounts.apt_cache = /var/cache/apt/archives
agent.docker_internal_mounts.ssh_folder = ~/.ssh
agent.docker_internal_mounts.ssh_ro_folder = /.ssh
agent.docker_internal_mounts.pip_cache = /root/.cache/pip
agent.docker_internal_mounts.poetry_cache = /root/.cache/pypoetry
agent.docker_internal_mounts.vcs_cache = /root/.clearml/vcs-cache
agent.docker_internal_mounts.venv_build = ~/.clearml/venvs-builds
agent.docker_internal_mounts.pip_download = /root/.clearml/pip-download-cache
agent.apply_environment = true
agent.apply_files = true
agent.custom_build_script =
agent.git_user =
agent.extra_docker_arguments.0 = --privileged
agent.extra_docker_shell_script.0 = apt-get install -y s3fs
agent.default_python = 3.8
agent.cuda_version = 116
agent.cudnn_version = 0

Executing task id [c9cc71be12cc4bd68b01bdd15f18ddab]:
repository =
branch =
version_num =
tag =
docker_cmd = nvidia/cuda:11.6.0-cudnn8-runtime-ubuntu20.04 --network host
entry_point = interactive_session.py
working_dir = .

clearml_agent: ERROR: ERROR: package manager "conda" selected, but 'conda' executable could not be located `

Thank you very much for your quick reply!

Gladly 🙂

Can you verify conda can be located by one of these two options?

By default, the agent will use the system PATH (env var) to locate conda, or will use which conda to try and locate the conda executable

Thank you very much for your quick reply! Im using mac on my local machine and the agent is running on a linux vm (debian)

Shouldn't matter, since this is done during the virtualenv installation - either on the machine the agent is running on (no docker), or inside the docker container

Thanks for this information! Then I know that it must have something to do with the conda installation. I will dig deeper on that and will post an update, if I’m successful - maybe it would be helpful for someone else in the future