File size: 2,912 Bytes
16628c8 |
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 |
import tensorflow as tf
from data.utils import clean_task_instruction, euler_to_quaternion, euler_to_rotation_matrix, \
rotation_matrix_to_ortho6d
def terminate_act_to_bool(terminate_act: tf.Tensor) -> tf.Tensor:
"""
Convert terminate action to a boolean, where True means terminate.
"""
return tf.equal(terminate_act, tf.constant(1.0, dtype=tf.float32))
def process_step(step: dict) -> dict:
"""
Unify the action format and clean the task instruction.
DO NOT use python list, use tf.TensorArray instead.
"""
# Convert raw action to our action
action = step['action']
action['terminate'] = terminate_act_to_bool(action['terminate_episode'])
eef_delta_pos = action['world_vector']
eef_ang=action['rotation_delta']
eef_ang = euler_to_quaternion(eef_ang)
grip_open=tf.reshape(tf.where(action['open_gripper'],1.0, 0.0),(1,))
# grip_open:tensor
# No base found
# Concatenate the action
arm_action=tf.concat([eef_delta_pos,eef_ang,grip_open],axis=0)
action['arm_concat']=arm_action
#base_action = tf.concat([base_delta_pos, base_delta_ang], axis=0)
#action['base_concat'] = base_action
# Write the action format
action['format']=tf.constant("eef_delta_pos_x,eef_delta_pos_y,eef_delta_pos_z,eef_delta_angle_x,eef_delta_angle_y,eef_delta_angle_z,eef_delta_angle_w,gripper_open")
# Convert raw state to our state
state= step['observation']
eef_pos=state['state'][:3]
eef_ang=state['state'][3:6]
eef_ang = euler_to_rotation_matrix(eef_ang)
eef_ang = rotation_matrix_to_ortho6d(eef_ang)
gripper_action=state['state'][6:]
# Concatenate the state
state['arm_concat']=tf.concat([eef_pos,eef_ang,gripper_action],axis=0)
# Write the state format
state['format'] = tf.constant(
"eef_pos_x,eef_pos_y,eef_pos_z,eef_angle_0,eef_angle_1,eef_angle_2,eef_angle_3,eef_angle_4,eef_angle_5,gripper_open")
# Clean the task instruction
# Define the replacements (old, new) as a dictionary
replacements = {
'_': ' ',
'1f': ' ',
'4f': ' ',
'-': ' ',
'50': ' ',
'55': ' ',
'56': ' ',
}
instr = step['observation']['natural_language_instruction']
instr = clean_task_instruction(instr, replacements)
step['observation']['natural_language_instruction'] = instr
return step
if __name__ == "__main__":
import tensorflow_datasets as tfds
from data.utils import dataset_to_path
DATASET_DIR = 'data/datasets/openx_embod/'
DATASET_NAME = 'bridge'
# Load the dataset
dataset = tfds.builder_from_directory(
builder_dir=dataset_to_path(
DATASET_NAME, DATASET_DIR))
dataset = dataset.as_dataset(split='all')
# Inspect the dataset
for episode in dataset:
for step in episode['steps']:
print(step)
|