# Copyright (c) OpenMMLab. All rights reserved.
_base_ = [
    'mmaction::_base_/models/tsn_r50.py', 'mmaction::_base_/default_runtime.py'
]

clip_len = 5
model = dict(
    backbone=dict(in_channels=2 * clip_len),
    data_preprocessor=dict(mean=[128], std=[128]))

# dataset settings
dataset_type = 'RawframeDataset'
data_root_val = 'data/kinetics400/rawframes_val'
ann_file_val = 'data/kinetics400/kinetics400_val_list_rawframes.txt'

file_client_args = dict(io_backend='disk')

test_pipeline = [
    dict(type='UntrimmedSampleFrames', clip_len=clip_len, clip_interval=16),
    dict(type='RawFrameDecode', **file_client_args),
    dict(type='Resize', scale=(-1, 256)),
    dict(type='CenterCrop', crop_size=256),
    dict(type='FormatShape', input_format='NCHW_Flow'),
    dict(type='PackActionInputs')
]

test_dataloader = dict(
    batch_size=1,
    num_workers=8,
    persistent_workers=True,
    sampler=dict(type='DefaultSampler', shuffle=False),
    dataset=dict(
        type=dataset_type,
        ann_file=ann_file_val,
        data_prefix=dict(img=data_root_val),
        pipeline=test_pipeline,
        filename_tmpl='{}_{:05d}.jpg',
        modality='Flow',
        test_mode=True))

test_evaluator = []

test_cfg = dict(type='TestLoop')