File size: 4,210 Bytes
2622c40 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 | # Data config: pusht — 100 Franka teleop demonstrations of the real-hardware
# Push-T task (HF dataset SleepMastger/pusht-manipulation), 32,131 frames at
# 10 Hz across 4 collection sessions. Converted to LeRobot v2.1 by
# lift2lerobot/convert_lift_hdf5_to_lerobot_v21.py (--fps 10) via the
# raw/pusht_layout symlink shim.
#
# Task string (deploy-critical, must byte-match at inference, NO trailing
# period): "push the T block to the target outline"
#
# DEGENERATE CHANNELS — read before changing norm settings.
# The teleop rig commanded translation only and the gripper stayed clamped on
# the pusher pen for the whole task, so 6 of the 15 numeric channels are
# constant across all 32,131 frames (measured, not assumed):
# action drx, dry, drz range 0.0
# action gripper range 0.0 (raw +1 -> (1-g)/2 -> 0.0)
# state gripL, gripR range 3.2e-05
# The dataset README warns this makes a min/max normalizer divide by zero.
# It does NOT here: SingleFieldLinearNormalizer (normalizer.py:96-118) has
# `ignore_dim = input_range < range_tol` with range_tol = 1e-4, which catches
# all six (the tightest, 3.2e-05, clears it by 3x) and gives them scale 1.0
# with offset -min instead of dividing by ~0. So an ignored dim normalizes to
# (x - min): exactly 0 for the four action dims whose raw range is exactly
# 0.0, and [0, 3.2e-05] for the two gripper state dims. Either way the output
# is finite and bounded by the raw range, i.e. below range_tol — negligible
# next to the +/-1 live channels. Verified end to end by preflight.py, not
# just read off the source. Keeping the full 7-dim action / 8-dim proprio
# costs nothing and keeps the architecture byte-identical to the dish_utensil
# and fruit runs, so results stay comparable. If you ever raise range_tol
# below 3.2e-05, the gripper state dims WILL go inf — don't.
#
# Staged by stage_pusht_local.sh to node-local /tmp (NOT /dev/shm — 853 wipe).
train:
_target_: fastwam.datasets.lerobot.robot_video_dataset.RobotVideoDataset
dataset_dirs:
- /tmp/george_pusht/pusht_lerobot_v21
shape_meta:
images:
- key: image
raw_shape: [3, 256, 256]
shape: [3, 224, 224]
- key: wrist_image
raw_shape: [3, 256, 256]
shape: [3, 224, 224]
action:
- key: default
raw_shape: 7 # before transform
shape: 7 # after transform
state:
- key: default
raw_shape: 8 # before transform
shape: 8 # after transform
num_frames: 33
global_sample_stride: 1
action_video_freq_ratio: 4 # 32 action, 9 video frames
video_size: [224, 448] # final resize video
camera_key: null
val_set_proportion: 0.0
is_training_set: true
skip_padding_as_possible: false
concat_multi_camera: "horizontal"
processor:
_target_: fastwam.datasets.lerobot.processors.fastwam_processor.FastWAMProcessor
shape_meta: ${data.train.shape_meta}
num_obs_steps: ${data.train.num_frames}
num_output_cameras: 2
action_output_dim: 7 # eef_pose (6) + gripper (1)
proprio_output_dim: 8 # eef_pose (6) + gripper (2)
delta_action_dim_mask:
# The raw HDF5 actions are ALREADY per-step deltas (dx,dy,dz in metres
# per 100 ms), so this mask is not a "convert to delta" switch — the
# processor only uses it to zero PADDED action steps on the dims where
# 0 is the neutral value (fastwam_processor.py:300-308).
default: [true, true, true, true, true, true, false] # eef poses are delta, gripper is not
# action & state normalization
action_state_transforms: null
use_stepwise_action_norm: False
norm_default_mode: min/max
norm_exception_mode: null
action_state_merger:
_target_: fastwam.datasets.lerobot.transforms.action_state_merger.ConcatLeftAlign
train_transforms:
- _target_: fastwam.datasets.lerobot.transforms.image.ToTensor
- _target_: torchvision.transforms.Resize
size: [224, 224]
val_transforms:
- _target_: fastwam.datasets.lerobot.transforms.image.ToTensor
- _target_: torchvision.transforms.Resize
size: [224, 224]
text_embedding_cache_dir: /tmp/george_pusht/pusht_text_embeds_cache
context_len: 128
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