If you're not sure which to choose, learn more about installing packages. Magenta installation using "pip install magenta" having errors even on fresh environments I have been attempting to install magenta on anaconda for a few days now, but every time I feel like I'm getting close to achieving an actual functional environment that can run it, I run into errors. tensorflow, We recommend using Anaconda to install it, but it can work in any standard Python environment. If you're going to use Magenta, you need to install it and its dependencies. Please try enabling it if you encounter problems. magenta alternatives and similar packages Based on the "Miscellaneous" category. During handling of the above exception, another exception occurred: Traceback (most recent call last): File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\site-packages\pip\_internal\cli\base_command.py", line 188, in _main status = self.run(options, args) File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\site-packages\pip\_internal\cli\req_command.py", line 185, in wrapper return func(self, options, args) File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\site-packages\pip\_internal\commands\install.py", line 333, in run reqs, check_supported_wheels=not options.target_dir File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\site-packages\pip\_internal\resolution\legacy\resolver.py", line 179, in resolve discovered_reqs.extend(self._resolve_one(requirement_set, req)) File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\site-packages\pip\_internal\resolution\legacy\resolver.py", line 362, in _resolve_one abstract_dist = self._get_abstract_dist_for(req_to_install) File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\site-packages\pip\_internal\resolution\legacy\resolver.py", line 314, in _get_abstract_dist_for abstract_dist = self.preparer.prepare_linked_requirement(req) File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\site-packages\pip\_internal\operations\prepare.py", line 469, in prepare_linked_requirement hashes=hashes, File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\site-packages\pip\_internal\operations\prepare.py", line 259, in unpack_url hashes=hashes, File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\site-packages\pip\_internal\operations\prepare.py", line 130, in get_http_url link, downloader, temp_dir.path, hashes File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\site-packages\pip\_internal\operations\prepare.py", line 281, in _download_http_url for chunk in download.chunks: File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\site-packages\pip\_internal\cli\progress_bars.py", line 166, in iter for x in it: File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\site-packages\pip\_internal\network\utils.py", line 39, in response_chunks decode_content=False, File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\site-packages\pip\_vendor\urllib3\response.py", line 564, in stream data = self.read(amt=amt, decode_content=decode_content) File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\site-packages\pip\_vendor\urllib3\response.py", line 529, in read raise IncompleteRead(self._fp_bytes_read, self.length_remaining) File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\contextlib.py", line 99, in __exit__ self.gen.throw(type, value, traceback) File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\site-packages\pip\_vendor\urllib3\response.py", line 430, in _error_catcher raise ReadTimeoutError(self._pool, None, "Read timed out. music, Download files. Some of the later examples will also download other dependencies (such as models and checkpoints) [ ] 1 cell hidden. Site map. We support Python 3 (>= 3.5). How to install magenta-gpu (if you don't have a CUDA enabled GPU, only install magenta) on Ubuntu 18.04. Software Development :: Libraries :: Python Modules. Today, I'm happy to announce that this project is complete! Maybe the dependency specs are just stricter than they need to be (tensorflow 2.2.0 probably runs fine with scipy 1.5)? all systems operational. For the Python TensorFlow implementations, see the main Magenta repo.. Even this option was recently dropped from Magenta GitHub installation instruction, but GitHub still keeps old version of the Magenta installation on Docker. , maximum recursion depth exceeded while calling a Python object, , ModuleNotFoundError: No module named 'nnabla'. | This JavaScript implementation of Magenta's musical note-based models uses TensorFlow.js for GPU-accelerated inference. machine, Python 3.6 is too new. Status: Some features may not work without JavaScript. !apt-get update -qq && apt-get install -qq libflui dsynth1 build-essential libasound2-dev libjack-dev !pip install -U magenta pyfluidsynth # Hack to allow python to pick up the newly-instal led fluidsynth lib. and also installing locally after downloading source from github and running. Aug 22, 2017. We recommend using Anaconda to install it, but it can work in any standard Python environment. Alternatively, view magenta alternatives based on common mentions on social networks and blogs. pip install magenta==0.4.0 Alternatively, if you want to install Magenta globally you can use the following shell commands to run an install script created by the Magenta team to simplify things: curl https://raw.githubusercontent.com/tensorflow/magenta/master/magenta/tools/magenta-install.sh > /tmp/magenta-install.sh bash /tmp/magenta-install.sh You can change your text to bold, italic, and underlined in Python. (tensorflow_gpu) C:\Users\xxxxx>pip install magentaCollecting magenta Using cached magenta-2.1.2-py3-none-any.whl (1.4 MB)Requirement already satisfied: numpy i @magenta/music. art, The author of this package has not provided a project description. One dependency of Magenta causes some headaches in particular: python-rtmidi. In this tutorial, we will be using this library to extract tag href links from the web-page HTML. We recommend using Anaconda to install it, but it can work in any standard Python environment. File type. Install dependencies: $ sudo apt-get install build-essential libasound2-dev libjack-dev $ pip install --pre python-rtmidi. In order to get the most out of Magenta you'll need the following modules: cuDNN/7.0.5-CUDA-9.0.176 - the version of Magenta installed by pip strictly requires CUDA 9.0 and cuDNN 7.0; an "oldish" Python. (tensorflow_gpu) C:\Users\xxxxx>pip install magentaCollecting magenta Using cached magenta-2.1.2-py3-none-any.whl (1.4 MB)Requirement already satisfied: numpy in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from magenta) (1.19.1)Collecting dm-sonnet Using cached dm_sonnet-2.0.0-py3-none-any.whl (254 kB)Requirement already satisfied: matplotlib>=1.5.3 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from magenta) (3.2.1)Requirement already satisfied: tensorflow in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from magenta) (2.1.0)Collecting tensorflow-datasets Using cached tensorflow_datasets-3.2.1-py3-none-any.whl (3.4 MB)Requirement already satisfied: scipy>=0.18.1 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from magenta) (1.5.0)Collecting python-rtmidi<1.2,>=1.1 Downloading python_rtmidi-1.1.2-cp36-cp36m-win_amd64.whl (79 kB) || 79 kB 36 kB/sCollecting dopamine-rl<=3.0.1 Using cached dopamine_rl-3.0.1-py3-none-any.whl (84 kB)Collecting pretty-midi>=0.2.6 Using cached pretty_midi-0.2.9.tar.gz (5.6 MB)Collecting sk-video Using cached sk_video-1.1.10-py2.py3-none-any.whl (2.3 MB)Requirement already satisfied: Pillow>=3.4.2 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from magenta) (7.1.2)Requirement already satisfied: six>=1.12.0 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from magenta) (1.15.0)Collecting sox>=1.3.7 Using cached sox-1.4.1-py2.py3-none-any.whl (39 kB)Collecting mido==1.2.6 Using cached mido-1.2.6-py2.py3-none-any.whl (69 kB)Collecting librosa<0.8.0,>=0.6.2 Using cached librosa-0.7.2.tar.gz (1.6 MB)Collecting tf-slim Using cached tf_slim-1.1.0-py2.py3-none-any.whl (352 kB)Requirement already satisfied: absl-py in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from magenta) (0.9.0)Collecting note-seq Using cached note_seq-0.0.1-py3-none-any.whl (209 kB)Collecting tensor2tensor Using cached tensor2tensor-1.15.7-py2.py3-none-any.whl (1.4 MB)Collecting scikit-image Downloading scikit_image-0.17.2-cp36-cp36m-win_amd64.whl (11.5 MB) || 11.5 MB 33 kB/sCollecting mir-eval>=0.4 Using cached mir_eval-0.6.tar.gz (87 kB)Requirement already satisfied: wheel in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from magenta) (0.34.2)Collecting tensorflow-probability Using cached tensorflow_probability-0.11.1-py2.py3-none-any.whl (4.3 MB)Collecting numba<0.50 Downloading numba-0.49.1-cp36-cp36m-win_amd64.whl (2.2 MB) || 2.2 MB 75 kB/sCollecting pygtrie>=2.3 Using cached pygtrie-2.3.3.tar.gz (34 kB)Collecting imageio Downloading imageio-2.9.0-py3-none-any.whl (3.3 MB) || 3.3 MB 21 kB/sRequirement already satisfied: wrapt>=1.11.1 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from dm-sonnet->magenta) (1.12.1)Collecting tabulate>=0.7.5 Using cached tabulate-0.8.7-py3-none-any.whl (24 kB)Collecting dm-tree>=0.1.1 Downloading dm_tree-0.1.5-cp36-cp36m-win_amd64.whl (85 kB) || 85 kB 81 kB/sRequirement already satisfied: cycler>=0.10 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from matplotlib>=1.5.3->magenta) (0.10.0)Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from matplotlib>=1.5.3->magenta) (2.4.7)Requirement already satisfied: python-dateutil>=2.1 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from matplotlib>=1.5.3->magenta) (2.8.1)Requirement already satisfied: kiwisolver>=1.0.1 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from matplotlib>=1.5.3->magenta) (1.2.0)Requirement already satisfied: keras-applications>=1.0.8 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from tensorflow->magenta) (1.0.8)Requirement already satisfied: gast==0.2.2 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from tensorflow->magenta) (0.2.2)Requirement already satisfied: opt-einsum>=2.3.2 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from tensorflow->magenta) (3.2.1)Requirement already satisfied: astor>=0.6.0 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from tensorflow->magenta) (0.8.1)Requirement already satisfied: termcolor>=1.1.0 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from tensorflow->magenta) (1.1.0)Requirement already satisfied: protobuf>=3.8.0 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from tensorflow->magenta) (3.12.3)Collecting tensorboard<2.2.0,>=2.1.0 Using cached tensorboard-2.1.1-py3-none-any.whl (3.8 MB)Requirement already satisfied: grpcio>=1.8.6 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from tensorflow->magenta) (1.28.1)Requirement already satisfied: google-pasta>=0.1.6 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from tensorflow->magenta) (0.2.0)Requirement already satisfied: keras-preprocessing>=1.1.0 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from tensorflow->magenta) (1.1.0)Requirement already satisfied: tensorflow-estimator<2.2.0,>=2.1.0rc0 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from tensorflow->magenta) (2.1.0)Requirement already satisfied: attrs>=18.1.0 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from tensorflow-datasets->magenta) (19.3.0)Collecting dill Downloading dill-0.3.2.zip (177 kB) || 177 kB 40 kB/sCollecting promise Using cached promise-2.3.tar.gz (19 kB)Requirement already satisfied: tqdm in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from tensorflow-datasets->magenta) (4.46.0)Collecting tensorflow-metadata Using cached tensorflow_metadata-0.24.0-py3-none-any.whl (44 kB)Collecting future Using cached future-0.18.2.tar.gz (829 kB)Requirement already satisfied: requests>=2.19.0 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from tensorflow-datasets->magenta) (2.24.0)Collecting gym>=0.10.5 Using cached gym-0.17.3.tar.gz (1.6 MB)Requirement already satisfied: opencv-python>=3.4.1.15 in c:\users\xxxxx\anaconda3\envs\tensorflow_gpu\lib\site-packages (from dopamine-rl<=3.0.1->magenta) (4.2.0.34)Collecting gin-config>=0.1.1 Using cached gin_config-0.3.0-py3-none-any.whl (44 kB)Collecting audioread>=2.0.0 Using cached audioread-2.1.8.tar.gz (21 kB)Collecting scikit-learn!=0.19.0,>=0.14.0 Downloading scikit_learn-0.23.2-cp36-cp36m-win_amd64.whl (6.8 MB) | | 2.1 MB 18 kB/s eta 0:04:13ERROR: Exception:Traceback (most recent call last): File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\site-packages\pip\_vendor\urllib3\response.py", line 425, in _error_catcher yield File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\site-packages\pip\_vendor\urllib3\response.py", line 507, in read data = self._fp.read(amt) if not fp_closed else b"" File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\site-packages\pip\_vendor\cachecontrol\filewrapper.py", line 62, in read data = self.__fp.read(amt) File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\http\client.py", line 459, in read n = self.readinto(b) File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\http\client.py", line 503, in readinto n = self.fp.readinto(b) File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\socket.py", line 586, in readinto return self._sock.recv_into(b) File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\ssl.py", line 1012, in recv_into return self.read(nbytes, buffer) File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\ssl.py", line 874, in read return self._sslobj.read(len, buffer) File "C:\Users\xxxxx\Anaconda3\envs\tensorflow_gpu\lib\ssl.py", line 631, in read v = self._sslobj.read(len, buffer)socket.timeout: The read operation timed out. If you have GPU on your machine, replace tensorflow with tensorflow-gpu. conda install -n new_env tensorflow=[tf_version] python=[python_version] magenta=[magenta_version] conda activate new_env should work. Developed and maintained by the Python community, for the Python community. pip install tensorflow-probability==0.8 pip install tensorflow-addons==0.6.0 Getting python-rtmidi to work. We recommend using Anaconda to install it, but it can work in any standard Python environment. Install pip install magenta==2.1.0 SourceRank 9. ")pip._vendor.urllib3.exceptions.ReadTimeoutError: HTTPSConnectionPool(host='files.pythonhosted.org', port=443): Read timed out. It's possible that this is a DCCN-specific thing again, so you could try to see what happens if you just omit this step and try to install Magenta immediately. Download the file for your platform. Summary: To print bold text in Python, you can use:The simple_color package,The 3[1m ANSI escape-sequence,The termcolor module,The coloroma package,The prompt_toolkit package. Pretty Print 2D Lists Using Tabulate. These instructions will assume you are using Anaconda. To create Ascii Art using Colorama first you have to install it with Pip. Download files. Install Colorama with Pip. In this chapter, we'll use the following tools: Python, Conda, and pip, to install and execute the Magenta environment Magenta, to test our setup by performing This website uses cookies and other tracking technology to analyse traffic, personalise ads and learn how we can improve the experience for our visitors and customers. 2021 Python Software Foundation Complete API documentation is available here.. Table of Contents Files for magenta-gpu, version 1.1.7. Dependencies 0 Dependent packages 0 Dependent repositories 35 Total releases 63 Latest release about 2 months ago First release Oct 5, 2016.
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