mirror of
https://github.com/amazon-science/chronos-forecasting
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222 lines
6.3 KiB
Python
222 lines
6.3 KiB
Python
NUM_YEARS = 5
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START_DATE = "01/01/2024"
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END_DATE = "12/31/2028"
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NUM_EVENTS_PER_YEAR = 25
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DATASETS_INFO = {
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"simple_spikes_mult": {
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"function_covariates": "steps",
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"op": "mult",
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"function_target": "simple",
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"delta": 2,
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"num_events": 4 * NUM_EVENTS_PER_YEAR * NUM_YEARS,
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"fixed_event_pos": 15,
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},
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"simple_spikes_add": {
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"function_covariates": "steps",
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"op": "add",
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"delta": 2,
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"function_target": "simple",
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"num_events": 4 * NUM_EVENTS_PER_YEAR * NUM_YEARS,
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"fixed_event_pos": 15,
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},
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"diverse_spikes_mult": {
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"function_covariates": "steps",
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"op": "mult",
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"delta": 2,
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"function_target": "diverse",
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"num_events": 4 * NUM_EVENTS_PER_YEAR * NUM_YEARS,
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"fixed_event_pos": 15,
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},
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"diverse_spikes_add": {
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"function_covariates": "steps",
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"op": "add",
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"delta": 2,
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"function_target": "diverse",
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"num_events": 4 * NUM_EVENTS_PER_YEAR * NUM_YEARS,
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"fixed_event_pos": 15,
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},
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"noisy_spikes_mult": {
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"function_covariates": "steps",
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"op": "mult",
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"delta": 2,
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"function_target": "noisy",
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"num_events": 4 * NUM_EVENTS_PER_YEAR * NUM_YEARS,
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"fixed_event_pos": 15,
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},
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"noisy_spikes_add": {
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"function_covariates": "steps",
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"op": "add",
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"delta": 2,
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"function_target": "noisy",
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"num_events": 4 * NUM_EVENTS_PER_YEAR * NUM_YEARS,
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"fixed_event_pos": 15,
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},
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"simple_steps_mult": {
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"function_covariates": "steps",
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"op": "mult",
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"function_target": "simple",
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"delta": 15,
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"num_events": NUM_EVENTS_PER_YEAR * NUM_YEARS,
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},
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"simple_steps_add": {
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"function_covariates": "steps",
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"op": "add",
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"function_target": "simple",
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"delta": 15,
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"num_events": NUM_EVENTS_PER_YEAR * NUM_YEARS,
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},
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"diverse_steps_mult": {
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"function_covariates": "steps",
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"op": "mult",
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"function_target": "diverse",
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"delta": 15,
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"num_events": NUM_EVENTS_PER_YEAR * NUM_YEARS,
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},
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"diverse_steps_add": {
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"function_covariates": "steps",
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"op": "add",
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"function_target": "diverse",
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"delta": 15,
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"num_events": NUM_EVENTS_PER_YEAR * NUM_YEARS,
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},
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"noisy_steps_mult": {
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"function_covariates": "steps",
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"op": "mult",
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"function_target": "noisy",
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"delta": 15,
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"num_events": NUM_EVENTS_PER_YEAR * NUM_YEARS,
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},
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"noisy_steps_add": {
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"function_covariates": "steps",
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"op": "add",
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"function_target": "noisy",
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"delta": 15,
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"num_events": NUM_EVENTS_PER_YEAR * NUM_YEARS,
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},
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"simple_bells_mult": {
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"function_covariates": "bells",
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"op": "mult",
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"function_target": "simple",
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"num_events": NUM_EVENTS_PER_YEAR * NUM_YEARS,
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"fixed_event_pos": 15,
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},
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"simple_bells_add": {
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"function_covariates": "bells",
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"op": "add",
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"function_target": "simple",
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"num_events": NUM_EVENTS_PER_YEAR * NUM_YEARS,
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"fixed_event_pos": 15,
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},
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"diverse_bells_mult": {
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"function_covariates": "bells",
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"op": "mult",
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"function_target": "diverse",
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"num_events": NUM_EVENTS_PER_YEAR * NUM_YEARS,
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"fixed_event_pos": 15,
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},
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"diverse_bells_add": {
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"function_covariates": "bells",
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"op": "add",
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"function_target": "diverse",
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"num_events": NUM_EVENTS_PER_YEAR * NUM_YEARS,
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"fixed_event_pos": 15,
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},
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"noisy_bells_mult": {
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"function_covariates": "bells",
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"op": "mult",
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"function_target": "noisy",
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"num_events": NUM_EVENTS_PER_YEAR * NUM_YEARS,
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"fixed_event_pos": 15,
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},
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"noisy_bells_add": {
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"function_covariates": "bells",
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"op": "add",
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"function_target": "noisy",
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"num_events": NUM_EVENTS_PER_YEAR * NUM_YEARS,
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"fixed_event_pos": 15,
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},
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"single_bells_mult": {
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"function_covariates": "bells",
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"op": "mult",
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"function_target": "single",
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"num_events": NUM_EVENTS_PER_YEAR * NUM_YEARS,
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"fixed_event_pos": 15,
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},
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"single_bells_add": {
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"function_covariates": "bells",
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"op": "add",
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"function_target": "single",
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"num_events": NUM_EVENTS_PER_YEAR * NUM_YEARS,
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"fixed_event_pos": 15,
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},
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"single_steps_mult": {
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"function_covariates": "steps",
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"op": "mult",
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"function_target": "single",
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"delta": 15,
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"num_events": NUM_EVENTS_PER_YEAR * NUM_YEARS,
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},
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"single_steps_add": {
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"function_covariates": "steps",
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"op": "add",
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"function_target": "single",
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"delta": 15,
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"num_events": NUM_EVENTS_PER_YEAR * NUM_YEARS,
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},
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"single_spikes_mult": {
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"function_covariates": "steps",
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"op": "mult",
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"function_target": "single",
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"delta": 2,
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"num_events": 4 * NUM_EVENTS_PER_YEAR * NUM_YEARS,
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"fixed_event_pos": 15,
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},
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"single_spikes_add": {
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"function_covariates": "steps",
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"op": "add",
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"function_target": "single",
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"delta": 2,
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"num_events": 4 * NUM_EVENTS_PER_YEAR * NUM_YEARS,
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"fixed_event_pos": 15,
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},
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"single_arp_mult": {
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"function_covariates": "arp",
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"op": "mult",
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"function_target": "single",
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},
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"single_arp_add": {
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"function_covariates": "arp",
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"op": "add",
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"function_target": "single",
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},
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"simple_arp_mult": {
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"function_covariates": "arp",
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"op": "mult",
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"function_target": "simple",
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},
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"simple_arp_add": {
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"function_covariates": "arp",
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"op": "add",
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"function_target": "simple",
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},
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"diverse_arp_mult": {
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"function_covariates": "arp",
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"op": "mult",
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"function_target": "diverse",
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},
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"diverse_arp_add": {
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"function_covariates": "arp",
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"op": "add",
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"function_target": "diverse",
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},
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"noisy_arp_mult": {
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"function_covariates": "arp",
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"op": "mult",
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"function_target": "noisy",
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},
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"noisy_arp_add": {
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"function_covariates": "arp",
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"op": "add",
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"function_target": "noisy",
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},
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}
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