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[air/preprocessors] Concatenator doesn't work for pandas==1.2.1 #27503

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richardliaw opened this issue Aug 4, 2022 · 1 comment · Fixed by #27531
Closed

[air/preprocessors] Concatenator doesn't work for pandas==1.2.1 #27503

richardliaw opened this issue Aug 4, 2022 · 1 comment · Fixed by #27531
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@clarkzinzow
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bug Something that is supposed to be working; but isn't P0 Issues that should be fixed in short order release-blocker P0 Issue that blocks the release

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@richardliaw
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What happened + What you expected to happen

Also... this is a terrible error message.

(TorchTrainer pid=88526) 2022-08-04 10:42:13,240        ERROR function_trainable.py:298 -- Runner Thread raised error.
(TorchTrainer pid=88526) Traceback (most recent call last):
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/tune/trainable/function_trainable.py", line 289, in run
(TorchTrainer pid=88526)     self._entrypoint()
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/tune/trainable/function_trainable.py", line 365, in entrypoint
(TorchTrainer pid=88526)     self._status_reporter.get_checkpoint(),
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/util/tracing/tracing_helper.py", line 466, in _resume_span
(TorchTrainer pid=88526)     return method(self, *_args, **_kwargs)
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/train/base_trainer.py", line 458, in _trainable_func
(TorchTrainer pid=88526)     super()._trainable_func(self._merged_config, reporter, checkpoint_dir)
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/tune/trainable/function_trainable.py", line 684, in _trainable_func
(TorchTrainer pid=88526)     output = fn()
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/train/base_trainer.py", line 372, in train_func
(TorchTrainer pid=88526)     trainer.preprocess_datasets()
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/train/data_parallel_trainer.py", line 300, in preprocess_datasets
(TorchTrainer pid=88526)     self.preprocessor, self.datasets
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/train/_internal/dataset_spec.py", line 153, in preprocess_datasets
(TorchTrainer pid=88526)     new_datasets[key] = prep.transform(dataset)
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/data/preprocessor.py", line 143, in transform
(TorchTrainer pid=88526)     transformed_ds = self._transform(dataset)
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/data/preprocessors/chain.py", line 64, in _transform
(TorchTrainer pid=88526)     ds = preprocessor.transform(ds)
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/data/preprocessor.py", line 143, in transform
(TorchTrainer pid=88526)     transformed_ds = self._transform(dataset)
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/data/preprocessor.py", line 234, in _transform
(TorchTrainer pid=88526)     return dataset.map_batches(self._transform_pandas, batch_format="pandas")
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/data/dataset.py", line 495, in map_batches
(TorchTrainer pid=88526)     return Dataset(plan, self._epoch, self._lazy)
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/data/dataset.py", line 201, in __init__
(TorchTrainer pid=88526)     self._plan.execute(allow_clear_input_blocks=False)
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/data/_internal/plan.py", line 309, in execute
(TorchTrainer pid=88526)     blocks, clear_input_blocks, self._run_by_consumer
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/data/_internal/plan.py", line 672, in __call__
(TorchTrainer pid=88526)     fn_constructor_kwargs=self.fn_constructor_kwargs,
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/data/_internal/compute.py", line 126, in _apply
(TorchTrainer pid=88526)     raise e from None
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/data/_internal/compute.py", line 113, in _apply
(TorchTrainer pid=88526)     results = map_bar.fetch_until_complete(refs)
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/data/_internal/progress_bar.py", line 75, in fetch_until_complete
(TorchTrainer pid=88526)     for ref, result in zip(done, ray.get(done)):
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/_private/client_mode_hook.py", line 105, in wrapper
(TorchTrainer pid=88526)     return func(*args, **kwargs)
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/_private/worker.py", line 2245, in get
(TorchTrainer pid=88526)     raise value.as_instanceof_cause()
(TorchTrainer pid=88526) ray.exceptions.RayTaskError(ValueError): ray::_map_block_nosplit() (pid=88535, ip=127.0.0.1)
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/data/_internal/compute.py", line 449, in _map_block_nosplit
(TorchTrainer pid=88526)     for new_block in block_fn(block, *fn_args, **fn_kwargs):
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/data/dataset.py", line 457, in transform
(TorchTrainer pid=88526)     applied = batch_fn(view, *fn_args, **fn_kwargs)
(TorchTrainer pid=88526)   File "/Users/rliaw/ray/python/ray/data/preprocessors/concatenator.py", line 94, in _transform_pandas
(TorchTrainer pid=88526)     df.loc[:, self.output_column_name] = list(concatenated)
(TorchTrainer pid=88526)   File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 692, in __setitem__
(TorchTrainer pid=88526)     iloc._setitem_with_indexer(indexer, value, self.name)
(TorchTrainer pid=88526)   File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 1604, in _setitem_with_indexer
(TorchTrainer pid=88526)     self._setitem_with_indexer(new_indexer, value, name)
(TorchTrainer pid=88526)   File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 1635, in _setitem_with_indexer
(TorchTrainer pid=88526)     self._setitem_with_indexer_split_path(indexer, value, name)
(TorchTrainer pid=88526)   File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 1672, in _setitem_with_indexer_split_path
(TorchTrainer pid=88526)     self._setitem_with_indexer_2d_value(indexer, value)
(TorchTrainer pid=88526)   File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 1733, in _setitem_with_indexer_2d_value
(TorchTrainer pid=88526)     "Must have equal len keys and value when setting with an ndarray"
(TorchTrainer pid=88526) ValueError: Must have equal len keys and value when setting with an ndarray
(_map_block_nosplit pid=88535) TOTAL LIST LEN 398
(_map_block_nosplit pid=88535) DF (398, 1)
(_map_block_nosplit pid=88535) 2022-08-04 10:42:13,238  INFO worker.py:754 -- Task failed with retryable exception: TaskID(c93105c99631c023ffffffffffffffffffffffff01000000).
(_map_block_nosplit pid=88535) Traceback (most recent call last):
(_map_block_nosplit pid=88535)   File "python/ray/_raylet.pyx", line 662, in ray._raylet.execute_task
(_map_block_nosplit pid=88535)   File "python/ray/_raylet.pyx", line 666, in ray._raylet.execute_task
(_map_block_nosplit pid=88535)   File "/Users/rliaw/ray/python/ray/data/_internal/compute.py", line 449, in _map_block_nosplit
(_map_block_nosplit pid=88535)     for new_block in block_fn(block, *fn_args, **fn_kwargs):
(_map_block_nosplit pid=88535)   File "/Users/rliaw/ray/python/ray/data/dataset.py", line 457, in transform
(_map_block_nosplit pid=88535)     applied = batch_fn(view, *fn_args, **fn_kwargs)
(_map_block_nosplit pid=88535)   File "/Users/rliaw/ray/python/ray/data/preprocessors/concatenator.py", line 94, in _transform_pandas
(_map_block_nosplit pid=88535)     df.loc[:, self.output_column_name] = list(concatenated)
(_map_block_nosplit pid=88535)   File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 692, in __setitem__
(_map_block_nosplit pid=88535)     iloc._setitem_with_indexer(indexer, value, self.name)
(_map_block_nosplit pid=88535)   File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 1604, in _setitem_with_indexer
(_map_block_nosplit pid=88535)     self._setitem_with_indexer(new_indexer, value, name)
(_map_block_nosplit pid=88535)   File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 1635, in _setitem_with_indexer
(_map_block_nosplit pid=88535)     self._setitem_with_indexer_split_path(indexer, value, name)
(_map_block_nosplit pid=88535)   File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 1672, in _setitem_with_indexer_split_path
(_map_block_nosplit pid=88535)     self._setitem_with_indexer_2d_value(indexer, value)
(_map_block_nosplit pid=88535)   File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 1733, in _setitem_with_indexer_2d_value
(_map_block_nosplit pid=88535)     "Must have equal len keys and value when setting with an ndarray"
(_map_block_nosplit pid=88535) ValueError: Must have equal len keys and value when setting with an ndarray
2022-08-04 10:42:13,450 ERROR trial_runner.py:980 -- Trial TorchTrainer_c1456_00000: Error processing event.
ray.exceptions.RayTaskError(ValueError): ray::TrainTrainable.train() (pid=88526, ip=127.0.0.1, repr=TorchTrainer)
  File "/Users/rliaw/ray/python/ray/tune/trainable/trainable.py", line 347, in train
    result = self.step()
  File "/Users/rliaw/ray/python/ray/tune/trainable/function_trainable.py", line 417, in step
    self._report_thread_runner_error(block=True)
  File "/Users/rliaw/ray/python/ray/tune/trainable/function_trainable.py", line 589, in _report_thread_runner_error
    raise e
  File "/Users/rliaw/ray/python/ray/tune/trainable/function_trainable.py", line 289, in run
    self._entrypoint()
  File "/Users/rliaw/ray/python/ray/tune/trainable/function_trainable.py", line 365, in entrypoint
    self._status_reporter.get_checkpoint(),
  File "/Users/rliaw/ray/python/ray/train/base_trainer.py", line 458, in _trainable_func
    super()._trainable_func(self._merged_config, reporter, checkpoint_dir)
  File "/Users/rliaw/ray/python/ray/tune/trainable/function_trainable.py", line 684, in _trainable_func
    output = fn()
  File "/Users/rliaw/ray/python/ray/train/base_trainer.py", line 372, in train_func
    trainer.preprocess_datasets()
  File "/Users/rliaw/ray/python/ray/train/data_parallel_trainer.py", line 300, in preprocess_datasets
    self.preprocessor, self.datasets
  File "/Users/rliaw/ray/python/ray/train/_internal/dataset_spec.py", line 153, in preprocess_datasets
    new_datasets[key] = prep.transform(dataset)
  File "/Users/rliaw/ray/python/ray/data/preprocessor.py", line 143, in transform
    transformed_ds = self._transform(dataset)
  File "/Users/rliaw/ray/python/ray/data/preprocessors/chain.py", line 64, in _transform
    ds = preprocessor.transform(ds)
  File "/Users/rliaw/ray/python/ray/data/preprocessor.py", line 143, in transform
    transformed_ds = self._transform(dataset)
  File "/Users/rliaw/ray/python/ray/data/preprocessor.py", line 234, in _transform
    return dataset.map_batches(self._transform_pandas, batch_format="pandas")
  File "/Users/rliaw/ray/python/ray/data/dataset.py", line 495, in map_batches
    return Dataset(plan, self._epoch, self._lazy)
  File "/Users/rliaw/ray/python/ray/data/dataset.py", line 201, in __init__
    self._plan.execute(allow_clear_input_blocks=False)
  File "/Users/rliaw/ray/python/ray/data/_internal/plan.py", line 309, in execute
    blocks, clear_input_blocks, self._run_by_consumer
  File "/Users/rliaw/ray/python/ray/data/_internal/plan.py", line 672, in __call__
    fn_constructor_kwargs=self.fn_constructor_kwargs,
  File "/Users/rliaw/ray/python/ray/data/_internal/compute.py", line 126, in _apply
    raise e from None
  File "/Users/rliaw/ray/python/ray/data/_internal/compute.py", line 113, in _apply
    results = map_bar.fetch_until_complete(refs)
  File "/Users/rliaw/ray/python/ray/data/_internal/progress_bar.py", line 75, in fetch_until_complete
    for ref, result in zip(done, ray.get(done)):
ray.exceptions.RayTaskError(ValueError): ray::_map_block_nosplit() (pid=88535, ip=127.0.0.1)
  File "/Users/rliaw/ray/python/ray/data/_internal/compute.py", line 449, in _map_block_nosplit
    for new_block in block_fn(block, *fn_args, **fn_kwargs):
  File "/Users/rliaw/ray/python/ray/data/dataset.py", line 457, in transform
    applied = batch_fn(view, *fn_args, **fn_kwargs)
  File "/Users/rliaw/ray/python/ray/data/preprocessors/concatenator.py", line 94, in _transform_pandas
    df.loc[:, self.output_column_name] = list(concatenated)
  File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 692, in __setitem__
    iloc._setitem_with_indexer(indexer, value, self.name)
  File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 1604, in _setitem_with_indexer
    self._setitem_with_indexer(new_indexer, value, name)
  File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 1635, in _setitem_with_indexer
    self._setitem_with_indexer_split_path(indexer, value, name)
  File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 1672, in _setitem_with_indexer_split_path
    self._setitem_with_indexer_2d_value(indexer, value)
  File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 1733, in _setitem_with_indexer_2d_value
    "Must have equal len keys and value when setting with an ndarray"
ValueError: Must have equal len keys and value when setting with an ndarray
Result for TorchTrainer_c1456_00000:
  date: 2022-08-04_10-42-07
  experiment_id: e77ebac889bb4883816946ccc51336bd
  hostname: Richards-MBP.local.meter
  node_ip: 127.0.0.1
  pid: 88526
  timestamp: 1659634927
  trial_id: c1456_00000
  
== Status ==
Current time: 2022-08-04 10:42:13 (running for 00:00:08.08)
Memory usage on this node: 26.7/64.0 GiB
Using FIFO scheduling algorithm.
Resources requested: 0/16 CPUs, 0/0 GPUs, 0.0/34.48 GiB heap, 0.0/2.0 GiB objects
Result logdir: /Users/rliaw/ray_results/TorchTrainer_2022-08-04_10-42-05
Number of trials: 1/1 (1 ERROR)
+--------------------------+----------+-----------------+
| Trial name               | status   | loc             |
|--------------------------+----------+-----------------|
| TorchTrainer_c1456_00000 | ERROR    | 127.0.0.1:88526 |
+--------------------------+----------+-----------------+
Number of errored trials: 1
+--------------------------+--------------+--------------------------------------------------------------------------------------------------------------------+
| Trial name               |   # failures | error file                                                                                                         |
|--------------------------+--------------+--------------------------------------------------------------------------------------------------------------------|
| TorchTrainer_c1456_00000 |            1 | /Users/rliaw/ray_results/TorchTrainer_2022-08-04_10-42-05/TorchTrainer_c1456_00000_0_2022-08-04_10-42-05/error.txt |
+--------------------------+--------------+--------------------------------------------------------------------------------------------------------------------+

2022-08-04 10:42:13,563 ERROR tune.py:754 -- Trials did not complete: [TorchTrainer_c1456_00000]
2022-08-04 10:42:13,563 INFO tune.py:759 -- Total run time: 8.32 seconds (8.08 seconds for the tuning loop).
Traceback (most recent call last):
  File "/Users/rliaw/ray/doc/source/ray-air/examples/pytorch_tabular_starter.py", line 118, in <module>
    result = trainer.fit()
  File "/Users/rliaw/ray/python/ray/train/base_trainer.py", line 347, in fit
    raise result.error
types.RayTaskError(ValueError): ray::TrainTrainable.train() (pid=88526, ip=127.0.0.1, repr=TorchTrainer)
  File "/Users/rliaw/ray/python/ray/tune/trainable/trainable.py", line 347, in train
    result = self.step()
  File "/Users/rliaw/ray/python/ray/tune/trainable/function_trainable.py", line 417, in step
    self._report_thread_runner_error(block=True)
  File "/Users/rliaw/ray/python/ray/tune/trainable/function_trainable.py", line 589, in _report_thread_runner_error
    raise e
  File "/Users/rliaw/ray/python/ray/tune/trainable/function_trainable.py", line 289, in run
    self._entrypoint()
  File "/Users/rliaw/ray/python/ray/tune/trainable/function_trainable.py", line 365, in entrypoint
    self._status_reporter.get_checkpoint(),
  File "/Users/rliaw/ray/python/ray/train/base_trainer.py", line 458, in _trainable_func
    super()._trainable_func(self._merged_config, reporter, checkpoint_dir)
  File "/Users/rliaw/ray/python/ray/tune/trainable/function_trainable.py", line 684, in _trainable_func
    output = fn()
  File "/Users/rliaw/ray/python/ray/train/base_trainer.py", line 372, in train_func
    trainer.preprocess_datasets()
  File "/Users/rliaw/ray/python/ray/train/data_parallel_trainer.py", line 300, in preprocess_datasets
    self.preprocessor, self.datasets
  File "/Users/rliaw/ray/python/ray/train/_internal/dataset_spec.py", line 153, in preprocess_datasets
    new_datasets[key] = prep.transform(dataset)
  File "/Users/rliaw/ray/python/ray/data/preprocessor.py", line 143, in transform
    transformed_ds = self._transform(dataset)
  File "/Users/rliaw/ray/python/ray/data/preprocessors/chain.py", line 64, in _transform
    ds = preprocessor.transform(ds)
  File "/Users/rliaw/ray/python/ray/data/preprocessor.py", line 143, in transform
    transformed_ds = self._transform(dataset)
  File "/Users/rliaw/ray/python/ray/data/preprocessor.py", line 234, in _transform
    return dataset.map_batches(self._transform_pandas, batch_format="pandas")
  File "/Users/rliaw/ray/python/ray/data/dataset.py", line 495, in map_batches
    return Dataset(plan, self._epoch, self._lazy)
  File "/Users/rliaw/ray/python/ray/data/dataset.py", line 201, in __init__
    self._plan.execute(allow_clear_input_blocks=False)
  File "/Users/rliaw/ray/python/ray/data/_internal/plan.py", line 309, in execute
    blocks, clear_input_blocks, self._run_by_consumer
  File "/Users/rliaw/ray/python/ray/data/_internal/plan.py", line 672, in __call__
    fn_constructor_kwargs=self.fn_constructor_kwargs,
  File "/Users/rliaw/ray/python/ray/data/_internal/compute.py", line 126, in _apply
    raise e from None
  File "/Users/rliaw/ray/python/ray/data/_internal/compute.py", line 113, in _apply
    results = map_bar.fetch_until_complete(refs)
  File "/Users/rliaw/ray/python/ray/data/_internal/progress_bar.py", line 75, in fetch_until_complete
    for ref, result in zip(done, ray.get(done)):
ray.exceptions.RayTaskError(ValueError): ray::_map_block_nosplit() (pid=88535, ip=127.0.0.1)
  File "/Users/rliaw/ray/python/ray/data/_internal/compute.py", line 449, in _map_block_nosplit
    for new_block in block_fn(block, *fn_args, **fn_kwargs):
  File "/Users/rliaw/ray/python/ray/data/dataset.py", line 457, in transform
    applied = batch_fn(view, *fn_args, **fn_kwargs)
  File "/Users/rliaw/ray/python/ray/data/preprocessors/concatenator.py", line 94, in _transform_pandas
    df.loc[:, self.output_column_name] = list(concatenated)
  File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 692, in __setitem__
    iloc._setitem_with_indexer(indexer, value, self.name)
  File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 1604, in _setitem_with_indexer
    self._setitem_with_indexer(new_indexer, value, name)
  File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 1635, in _setitem_with_indexer
    self._setitem_with_indexer_split_path(indexer, value, name)
  File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 1672, in _setitem_with_indexer_split_path
    self._setitem_with_indexer_2d_value(indexer, value)
  File "/Users/rliaw/miniconda3/envs/raybuild/lib/python3.7/site-packages/pandas/core/indexing.py", line 1733, in _setitem_with_indexer_2d_value
    "Must have equal len keys and value when setting with an ndarray"
ValueError: Must have equal len keys and value when setting with an ndarray

Versions / Dependencies

pandas==1.2.1
ray==2.0rc0 or master

Reproduction script

import ray
import numpy as np
import pandas as pd

from ray.data.preprocessors import StandardScaler
from ray.air.config import ScalingConfig

from ray.data.preprocessors import Concatenator, Chain

# Load data.
dataset = ray.data.read_csv("s3://anonymous@air-example-data/breast_cancer.csv")

# Split data into train and validation.
train_dataset, valid_dataset = dataset.train_test_split(test_size=0.3)

# Create a preprocessor to scale some columns
columns_to_scale = ["mean radius", "mean texture"]
preprocessor = StandardScaler(columns=columns_to_scale)

preprocessor = Chain(
    preprocessor,
    Concatenator(exclude=["target"], dtype=np.float32),
)

preprocessor.fit_transform(train_dataset)

Issue Severity

High: It blocks me from completing my task.
@richardliaw richardliaw added bug Something that is supposed to be working; but isn't release-blocker P0 Issue that blocks the release P0 Issues that should be fixed in short order labels Aug 4, 2022
@richardliaw
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Works for latest version of pandas, which is what we test in CI.

@clarkzinzow clarkzinzow mentioned this issue Aug 4, 2022
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[AIR - Datasets] Fix column assignment in Concatenator for Pandas 1.2. clarkzinzow/ray
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@richardliaw @clarkzinzow