MCPcopy Create free account

hub / github.com/apple/axlearn / endpoints

Endpoints180 in github.com/apple/axlearn

⨍ Functions 7,799◇ Types & classes 2,118↳ Endpoints 180
Routetest_make_glue_autoregressive_inputs
parameterized.parameters( # Each test ensures that: # 1. "source_ids" ends with EOS; #
axlearn/common/input_glue_test.py:None
Routetest_make_t5_autoregressive_inputs
parameterized.parameters( # Test a basic input. dict( examples=[ d
axlearn/common/input_t5_test.py:None
Routetest_map_label_sequences
parameterized.parameters( dict( inputs=jnp.asarray( [
axlearn/audio/decoder_asr_test.py:None
Routetest_map_prefix_to_value
parameterized.parameters( # Packed input. dict( is_training=True, exam
axlearn/common/input_t5_test.py:None
Routetest_mask_generation
parameterized.product( num_masking_patches=(0, 118, 196), max_aspect=(None, 0.8, 10.0),
axlearn/vision/mask_generator_test.py:None
Routetest_maybe_monitor_all
mock.patch("jax.process_index", return_value=0)
axlearn/cloud/gcp/measurement_test.py:None
Routetest_maybe_monitor_goodput
mock.patch("jax.process_index", return_value=0)
axlearn/cloud/gcp/measurement_test.py:None
Routetest_maybe_monitor_rolling_window
mock.patch("jax.process_index", return_value=0)
axlearn/cloud/gcp/measurement_test.py:None
Routetest_maybe_pad_inputs
parameterized.parameters( dict(block_size=8, input_len=7, output_len=8), dict(block_size=8, in
axlearn/common/flash_attention/common_test.py:None
Routetest_mean_squared_error
parameterized.parameters( ([], [], WeightedSummary(0, 0), None), # No targets. (
axlearn/common/loss_test.py:None
Routetest_multi_layers
parameterized.parameters( dict( window=5, stride=2, conv_padding=(
axlearn/audio/subsamplers_test.py:None
Routetest_multiple_sequence_truncation
parameterized.parameters( { "max_len": 4, "examples": [ {"inpu
axlearn/common/input_glue_test.py:None
Routetest_noise_span_to_unique_sentinel
parameterized.parameters( # Test an empty input. dict( input_ids=tf.constant([]),
axlearn/common/input_t5_test.py:None
Routetest_non_zero_process_index_skips_monitoring
mock.patch("jax.process_index", return_value=1)
axlearn/cloud/gcp/measurement_test.py:None
Routetest_nonnoise_span_to_unique_sentinel
parameterized.parameters( # Test an empty input. dict( input_ids=tf.constant([]),
axlearn/common/input_t5_test.py:None
Routetest_normalize
parameterized.parameters( dict( normalizer=config_for_function(input_text.roberta_normaliz
axlearn/common/input_text_test.py:None
Routetest_normalize_ragged_input
parameterized.parameters( dict( normalizer=config_for_function(input_text.roberta_normaliz
axlearn/common/input_text_test.py:None
Routetest_num_params
parameterized.product( input_dim=(2, 9), output_dim=(13, 8), dw_kernel_size=(1, 3),
axlearn/vision/fpn_test.py:None
Routetest_output_shape
parameterized.parameters( dict(input_shape=(), output_dim=5, expected=ValueError("input_shape")),
axlearn/audio/subsamplers_test.py:None
Routetest_pack_to_batch
parameterized.parameters( dict( examples=[ {"a": tf.constant([[1, 0, 0], [
axlearn/common/input_tf_data_test.py:None
Routetest_packing
parameterized.parameters( # Note: Inputs will be detokenized into strings before feeding into the proc
axlearn/common/input_lm_test.py:None
Routetest_paged_attention_against_ref
parameterized.product( [ dict(zip(["batch_size", "seq_len", "num_heads", "per_head_dim"],
axlearn/common/flash_attention/decoding_test.py:None
Routetest_partition_by_path_rank
parameterized.parameters( dict( config={ (".*", 2): PartitionSpec("data",
axlearn/common/input_base_test.py:None
Routetest_post_batch_map_fn
parameterized.product( is_training=(False, True), post_batch_processor=(None, lambda x: x),
axlearn/common/input_tf_data_test.py:None
Routetest_pre_emphasis
parameterized.product( # Inputs are [batch, num_frames, frame_size]. input_shape=[(5, 1298, 40
axlearn/audio/frontend_utils_test.py:None
Routetest_prefill_states
parameterized.product( dtype=(jnp.float32, jnp.float16, jnp.bfloat16), per_dim_scale=(None, Pe
axlearn/common/attention_test.py:None
Routetest_prompt
parameterized.parameters( # Test basic required case. dict(required=True, inputs=[""], default
axlearn/cloud/common/config_test.py:None
Routetest_prompt_choice
parameterized.parameters( # Test no choices. dict(choices=[], inputs=[], expected=None),
axlearn/cloud/common/config_test.py:None
Routetest_prompt_project
parameterized.parameters( # Test basic case. dict(inputs=["0"], expected="project0"),
axlearn/cloud/common/config_test.py:None
Routetest_publish_success
mock.patch("pika.BlockingConnection")
axlearn/cloud/common/event_queue_test.py:None
Routetest_qlinear
parameterized.parameters( (QKVLinear.default_config(), QLinear.default_config()), (
axlearn/common/attention_test.py:None
Routetest_random_spans_noise_mask
parameterized.parameters( # Test some basic cases. dict( noise_density=0,
axlearn/common/input_t5_test.py:None
Routetest_rank_by_value
parameterized.parameters( { "input_sequence": [0.2, 0.9, 0.5, 0.8, 0.7], "expe
axlearn/common/input_ranking_test.py:None
Routetest_rearrange_invalid_pattern
parameterized.parameters( ("a b -> a", ValueError("Mismatch between LHS axes and RHS axes: {'a'} vs .*
axlearn/common/ein_ops_test.py:None
Routetest_record_event_context_manager_success
parameterized.parameters( dict( event=measurement.EventType.JOB, expected_star
axlearn/cloud/gcp/measurement_test.py:None
Routetest_record_event_works_with_monitoring_disabled
mock.patch("jax.process_index", return_value=0)
axlearn/cloud/gcp/measurement_test.py:None
Routetest_reduce_concat_tokens
parameterized.parameters( # Test a basic case with num_examples % batch_size == 0. dict(
axlearn/common/input_t5_test.py:None
Routetest_repeat
parameterized.product( dtype=(jnp.float32, jnp.bfloat16), remat_spec=( None,
axlearn/common/repeat_test.py:None
Routetest_replicated_job
parameterized.product( num_replicas=[1, 2], user_command_patcher=[None, MockUserCommandPatcher.default
axlearn/cloud/gcp/pathways_utils_test.py:None
Routetest_reschedule
parameterized.parameters( # Don't need to reschedule if no node-pool exists. dict(node_pool_by
axlearn/cloud/gcp/runners/gke_test.py:None
Routetest_rms_norm_partition_specs_constraint
mock.patch("axlearn.common.utils.with_sharding_constraint")
axlearn/common/layers_test.py:None
Routetest_roformer_qkv_linear
parameterized.product( dtype=(jnp.float32, jnp.bfloat16), input_linear=( None,
axlearn/common/attention_test.py:None
Routetest_schedule
parameterized.named_parameters( # Test a case where all jobs fit into tier 0. dict(
axlearn/cloud/common/scheduler_test.py:None
Routetest_segment_ids
parameterized.parameters( dict(window=3, stride=2, conv_padding=(1, 1), output_dim=10), dict(w
axlearn/audio/subsamplers_test.py:None
Routetest_segment_ids_from_causal_input_ids
parameterized.parameters( dict( input_ids=jnp.array( [
axlearn/common/decoder_test.py:None
Routetest_send_signal_with_children_no_such_process
mock.patch("psutil.Process")
axlearn/cloud/common/utils_test.py:None
Routetest_separable_space_time_positional_embedding
parameterized.named_parameters( { "testcase_name": "simple", "positions": None
axlearn/common/layers_test.py:None
Routetest_sequence_to_space_with_scaling
parameterized.product( num_cls_tokens=(0, 1), target_space_len=(None, 10, 14, 16), )
axlearn/common/vision_transformer_test.py:None
Routetest_set_attn_partition_specs
parameterized.product( input_linear_cfg=( QKVLinear.default_config(), FusedQKV
axlearn/common/attention_test.py:None
Routetest_set_double_shard_weights_config
parameterized.product( self_attention_input_linear_cfg=( QKVLinear.default_config(),
axlearn/common/attention_test.py:None
Routetest_set_double_shard_weights_config_for_list_of_configs
parameterized.product( self_attention_input_linear_cfg=( QKVLinear.default_config(),
axlearn/common/attention_test.py:None
Routetest_sliding_window
parameterized.product( base_cfg=( attention.MultiheadAttention.default_config(),
axlearn/common/attention_test.py:None
Routetest_small_input
parameterized.product(input_dtype=[jnp.bfloat16, jnp.float32, jnp.float64, jnp.int32])
axlearn/audio/frontend_test.py:None
Routetest_spectrum_augmenter
parameterized.product( [ dict( max_freq_masks=3, max_freq_
axlearn/audio/spectrum_augmenter_test.py:None
Routetest_speech_input
parameterized.parameters( dict( # Test a basic case with padding. max_len=5,
axlearn/audio/input_asr_test.py:None
Routetest_split_subsets
parameterized.product( causal=[ None, attention_bias.CausalAttentionBias(
axlearn/common/attention_bias_test.py:None
Routetest_text_input
parameterized.parameters( dict( # A basic case with padding (no truncation). t
axlearn/audio/input_asr_test.py:None
Routetest_tfds_decoders_ci
parameterized.parameters( ("inputs_pretokenized"), ("prefix_ids"), )
axlearn/common/input_tf_data_test.py:None
Routetest_to_splash_mask
parameterized.parameters( [ZeroAttentionBias(), splash_attention_mask.FullMask((8, 8))], [
axlearn/common/flash_attention/tpu_attention_test.py:None
Routetest_tpu_flags
parameterized.product( [ dict( name=None, output_dir=None,
axlearn/cloud/gcp/jobs/launch_test.py:None
Routetest_trim_and_pack_to_batch
parameterized.parameters( dict( examples=[ {"a": tf.constant([[1, 0, 0], [
axlearn/common/input_tf_data_test.py:None
Routetest_trim_and_pack_with_segments
parameterized.parameters( # Test packing with intermediate zeros. { "max_source_le
axlearn/common/input_lm_test.py:None
Routetest_trim_and_pad_non_zero_pad_id
parameterized.parameters( { "pad_id": -1, "max_len": 3, "input_ten
axlearn/common/input_tf_data_test.py:None
Routetest_trim_and_pad_tensor
parameterized.product( [ { "max_len": 7, "expected_tensor"
axlearn/common/input_tf_data_test.py:None
Routetest_trim_and_pad_tensor_nd
parameterized.parameters( { "input_tensor": tf.ragged.constant( [
axlearn/common/input_tf_data_test.py:None
Routetest_truncation_incompatible_shape
parameterized.parameters( ["truncate", "truncate_left", "keep_target", "replace_target_prefix_with_sou
axlearn/common/state_builder_test.py:None
Routetest_update_jobs_with_mock_scheduler
parameterized.parameters( # Test case 1: Simple PENDING -> ACTIVE transition dict(
axlearn/cloud/common/bastion_test.py:None
Routetest_uploader_calls
mock.patch("resource.setrlimit")
axlearn/cloud/gcp/vertexai_tensorboard_test.py:None
Routetest_v2_structure
parameterized.product( structure=("prenorm", "postnorm", "hybridnorm"), with_source=(False, True)
axlearn/common/attention_test.py:None
Routetest_v2_structure
parameterized.product( structure=("prenorm", "postnorm", "hybridnorm"), is_training=(True, Fal
axlearn/common/mixture_of_experts_test.py:None
Routetest_visualize
parameterized.product( [ dict( max_freq_masks=3, max_freq_
axlearn/audio/spectrum_augmenter_test.py:None
Routetest_window
parameterized.product( # Inputs are [batch, num_frames, frame_size]. input_shape=[(5, 1298, 40
axlearn/audio/frontend_utils_test.py:None
Routetest_window_partition_unpartition_with_num_windows
parameterized.parameters( [ dict( inputs_shape=[2, 112, 112, 3],
axlearn/vision/window_attention_test.py:None
Routetest_window_partition_with_window_size
parameterized.parameters( [ dict( inputs_shape=[2, 100, 100, 3],
axlearn/vision/window_attention_test.py:None
Routetest_window_unpartition_with_window_size
parameterized.parameters( [ dict( inputs_shape=[128, 14, 14, 3],
axlearn/vision/window_attention_test.py:None
Routetest_windowed_attention_forward
parameterized.parameters( [ dict(image_size=224, patch_size=16, use_rel_pos_emb=True),
axlearn/vision/attention_test.py:None
Routetest_windowed_attention_layer_forward
parameterized.parameters( [ dict(target_len=196, window_size=14), dict(target_
axlearn/vision/attention_test.py:None
Routetest_windowed_packing_streaming_packing_parity
parameterized.parameters( dict( target_labels=[ np.array([33, 33]),
axlearn/common/input_grain_lm_test.py:None
Routetest_word_error_rate_metrics
parameterized.parameters( [ # Basic cases. dict( references=[
axlearn/audio/evaler_asr_test.py:None
Routewrapper
partial( jax.shard_map, mesh=get_current_abstract_or_physical_mesh(), in_s
axlearn/common/mixture_of_experts.py:None
← previous101–180 of 180, ranked by callers