mars
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Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
**Is your feature request related to a problem? Please describe.** We currently support all scipy special error functions and fresnel integrals except ```fresnel_zeros```, so it would be good to support...
**Describe the bug** session creation error **To Reproduce** To help us reproducing this bug, please provide information below: 1. Python 3.7.13 2. Mars 9.0 3. // 4. Full stack of...
ENV: python 3.7.11 mars 0.9.0 ```Python import mars import mars.tensor as mt n = 20000 n_worker = 1 n_cpu = 1 mem_bytes = 20 * 2 ** 30 mars.new_session(init_local=True, n_worker=n_worker,...
**Describe the bug** A clear and concise description of what the bug is. **To Reproduce** To help us reproducing this bug, please provide information below: 1. Your Python version 2....
**Describe the bug** When executing a blockwise operations in mars which have many setitem/getitem nodes, mars will take about 1 minutes, which is too long. **To Reproduce** To help us...
**Describe the bug** When access task status for ray DAG mode in mars dashboard, got incorrect task status. Following task is finished, the graph should be green instead of blank:...
Implements Kronecker product for tensors, just as `numpy.kron` does. This is required by module `tensorly`.
Currently the following snippets causes error, which is quite surprising for users coming from Pandas background: ```python import mars.dataframe as md import mars.tensor as mt df = md.DataFrame(mt.random.randn(10, 4)) df.loc[df.index].execute()...
**Describe the bug** ```python import numpy as np import mars import mars.tensor as mt from mars.utils import new_random_id mars.new_session() s = np.array([new_random_id(20) for _ in range(10)]) target = s[5] print(target...
**Is your feature request related to a problem? Please describe.** Random forest classifier is widely used and should be introduced. The related scikit-learn API is https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html#sklearn.ensemble.RandomForestClassifier