Special remat for Neuron

axlearn/common/attention.py

@@ -3956,15 +3956,22 @@ def policy(prim, *_, **params):
     return policy
 
 
-SELF_ATTENTION_SAVE_PATTERN = ".*([qkvo]_proj|context)"
-FEED_FORWARD_SAVE_PATTERN = ".*linear[12]_.*"
+# Regex patterns for matching remat names
+class RematRegexSavePatterns(enum.Enum):
+    QKV_PROJ = r".*[kqv]_proj"
+    O_PROJ = r".*o_proj"
+    CONTEXT = r".*context"
+    LINEAR1_X = r".*linear1_[01]"
+    LINEAR2_X = r".*linear2_[01]"
+    SELF_ATTENTION = re.compile("|".join([QKV_PROJ, O_PROJ, CONTEXT])).pattern
+    FEED_FORWARD = re.compile("|".join([LINEAR1_X, LINEAR2_X])).pattern
 
 
 def build_remat_spec(
     stack_cfg: Union[
         BaseStackedTransformerLayer.Config, "RepeatedConformerLayer.Config"  # type: ignore
     ],
-    save_pattern: _SavePattern = SELF_ATTENTION_SAVE_PATTERN,
+    save_pattern: _SavePattern = RematRegexSavePatterns.SELF_ATTENTION.value,
     offload_pattern: _SavePattern = None,
     offload_dst: str = "pinned_host",
 ) -> Optional[RematSpec]:

axlearn/common/attention_test.py

@@ -41,7 +41,6 @@
 
 from axlearn.common import attention, attention_bias, test_utils, utils
 from axlearn.common.attention import (
-    FEED_FORWARD_SAVE_PATTERN,
     BaseStackedTransformerLayer,
     BaseTransformerLayer,
     BottleNeckAdapterTransformerLayer,
@@ -58,6 +57,7 @@
     PipelinedTransformerLayer,
     QKVLinear,
     QLinear,
+    RematRegexSavePatterns,
     RepeatedTransformerLayer,
     RoFormerQKVLinear,
     StackedTransformerLayer,
@@ -3420,7 +3420,7 @@ def f(x, layer_params):
             jax.remat(
                 f,
                 policy=_save_and_offload_only_these_names_regex(
-                    names_which_can_be_saved=FEED_FORWARD_SAVE_PATTERN,
+                    names_which_can_be_saved=RematRegexSavePatterns.FEED_FORWARD.value,
                     names_which_can_be_offloaded=None,
                     offload_src="device",
                     offload_dst="pinned_host",
@@ -3875,6 +3875,70 @@ def f(x, layer_params):
             5,
         )
 
+    def test_build_remat_spec_neuron(self):
+        model_dim, num_heads = 6, 2
+        cfg: TransformerLayer.Config = TransformerLayer.default_config().set(input_dim=model_dim)
+        cfg.self_attention.attention.set(num_heads=num_heads, causal=True)
+        cfg.feed_forward.hidden_dim = model_dim * 4
+        cfg.vlog = 5
+
+        layer: BaseTransformerLayer = cfg.clone(name="layer").instantiate(parent=None)
+        layer_params = layer.initialize_parameters_recursively(prng_key=jax.random.PRNGKey(0))
+
+        batch_size, tgt_len = 2, 5
+        rng = np.random.default_rng(seed=123)
+        target = rng.random([batch_size, tgt_len, cfg.input_dim], dtype=np.float32)
+
+        def f(x, layer_params):
+            forward_outputs, _ = F(
+                layer,
+                inputs=dict(
+                    data=x,
+                ),
+                state=layer_params,
+                is_training=True,
+                prng_key=jax.random.PRNGKey(0),
+            )
+            return forward_outputs
+
+        # Ignore type errors.
+        spec: Any = build_remat_spec(mock.MagicMock())
+
+        policy = (
+            config_for_function(_save_and_offload_only_these_names_regex)
+            .set(
+                names_which_can_be_saved="|".join(
+                    [
+                        RematRegexSavePatterns.QKV_PROJ.value,
+                        RematRegexSavePatterns.LINEAR1_X.value,
+                    ]
+                ),
+                names_which_can_be_offloaded=None,
+                offload_src=None,
+                offload_dst=None,
+            )
+            .instantiate()
+        )
+
+        _, default_policy_backward = jax.linearize(
+            jax.remat(f, policy=policy, prevent_cse=spec.prevent_cse),
+            jnp.asarray(target),
+            layer_params,
+        )
+        _, full_remat_backward = jax.linearize(
+            jax.remat(f),
+            jnp.asarray(target),
+            layer_params,
+        )
+
+        # Eliminated the remat of qkv_proj and linear1_0 = 4 dots. This assumes
+        # FlashAttention is not enabled.
+        self.assertEqual(
+            str(full_remat_backward).count(" dot_general")
+            - str(default_policy_backward).count(" dot_general"),
+            4,
+        )
+
 
 class TestStackModel(BaseLayer):
     """A dummy transformer stack."""

axlearn/experiments/testdata/axlearn.experiments.audio.conformer.librispeech_trainer/conformer-l-rnnt.txt

@@ -485,7 +485,7 @@ model.encoder.context.context.num_layers: 17
 model.encoder.context.context.remat_spec['prevent_cse']: False
 model.encoder.context.context.remat_spec['policy'].fn: 'axlearn.common.attention._save_and_offload_only_these_names_regex'
 model.encoder.context.context.remat_spec['policy'].names_which_can_be_offloaded: None
-model.encoder.context.context.remat_spec['policy'].names_which_can_be_saved: '.*([qkvo]_proj|context)'
+model.encoder.context.context.remat_spec['policy'].names_which_can_be_saved: '.*[kqv]_proj|.*o_proj|.*context'
 model.encoder.context.context.remat_spec['policy'].offload_dst: 'pinned_host'
 model.encoder.context.context.remat_spec['policy'].offload_src: 'device'
 model.encoder.context.context.repeat.drop_output.fn: 'axlearn.common.repeat._drop_by_regex'

axlearn/experiments/testdata/axlearn.experiments.audio.conformer.librispeech_trainer/conformer-test-ctc.txt

@@ -188,7 +188,7 @@ model.encoder.context.context.num_layers: 1
 model.encoder.context.context.remat_spec['prevent_cse']: False
 model.encoder.context.context.remat_spec['policy'].fn: 'axlearn.common.attention._save_and_offload_only_these_names_regex'
 model.encoder.context.context.remat_spec['policy'].names_which_can_be_offloaded: None
-model.encoder.context.context.remat_spec['policy'].names_which_can_be_saved: '.*([qkvo]_proj|context)'
+model.encoder.context.context.remat_spec['policy'].names_which_can_be_saved: '.*[kqv]_proj|.*o_proj|.*context'
 model.encoder.context.context.remat_spec['policy'].offload_dst: 'pinned_host'
 model.encoder.context.context.remat_spec['policy'].offload_src: 'device'
 model.encoder.context.context.repeat.drop_output.fn: 'axlearn.common.repeat._drop_by_regex'

axlearn/experiments/testdata/axlearn.experiments.text.gpt.c4_trainer/fuji-1B-v3-flash-single-host.txt

@@ -188,7 +188,7 @@ model.decoder.transformer.layer.klass: 'axlearn.common.attention.TransformerLaye
 model.decoder.transformer.layer.remat_spec['prevent_cse']: False
 model.decoder.transformer.layer.remat_spec['policy'].fn: 'axlearn.common.attention._save_and_offload_only_these_names_regex'
 model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_offloaded: None
-model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*([qkvo]_proj|context)'
+model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*[kqv]_proj|.*o_proj|.*context'
 model.decoder.transformer.layer.remat_spec['policy'].offload_dst: 'pinned_host'
 model.decoder.transformer.layer.remat_spec['policy'].offload_src: 'device'
 model.decoder.transformer.layer.self_attention.attention.causal: True

axlearn/experiments/testdata/axlearn.experiments.text.gpt.c4_trainer/fuji-1B-v3-flash.txt

@@ -188,7 +188,7 @@ model.decoder.transformer.layer.klass: 'axlearn.common.attention.TransformerLaye
 model.decoder.transformer.layer.remat_spec['prevent_cse']: False
 model.decoder.transformer.layer.remat_spec['policy'].fn: 'axlearn.common.attention._save_and_offload_only_these_names_regex'
 model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_offloaded: None
-model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*([qkvo]_proj|context)'
+model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*[kqv]_proj|.*o_proj|.*context'
 model.decoder.transformer.layer.remat_spec['policy'].offload_dst: 'pinned_host'
 model.decoder.transformer.layer.remat_spec['policy'].offload_src: 'device'
 model.decoder.transformer.layer.self_attention.attention.causal: True

axlearn/experiments/testdata/axlearn.experiments.text.gpt.c4_trainer/fuji-1B-v3-single-host.txt

@@ -188,7 +188,7 @@ model.decoder.transformer.layer.klass: 'axlearn.common.attention.TransformerLaye
 model.decoder.transformer.layer.remat_spec['prevent_cse']: False
 model.decoder.transformer.layer.remat_spec['policy'].fn: 'axlearn.common.attention._save_and_offload_only_these_names_regex'
 model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_offloaded: None
-model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*([qkvo]_proj|context)'
+model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*[kqv]_proj|.*o_proj|.*context'
 model.decoder.transformer.layer.remat_spec['policy'].offload_dst: 'pinned_host'
 model.decoder.transformer.layer.remat_spec['policy'].offload_src: 'device'
 model.decoder.transformer.layer.self_attention.attention.causal: True

axlearn/experiments/testdata/axlearn.experiments.text.gpt.c4_trainer/fuji-1B-v3.txt

@@ -188,7 +188,7 @@ model.decoder.transformer.layer.klass: 'axlearn.common.attention.TransformerLaye
 model.decoder.transformer.layer.remat_spec['prevent_cse']: False
 model.decoder.transformer.layer.remat_spec['policy'].fn: 'axlearn.common.attention._save_and_offload_only_these_names_regex'
 model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_offloaded: None
-model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*([qkvo]_proj|context)'
+model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*[kqv]_proj|.*o_proj|.*context'
 model.decoder.transformer.layer.remat_spec['policy'].offload_dst: 'pinned_host'
 model.decoder.transformer.layer.remat_spec['policy'].offload_src: 'device'
 model.decoder.transformer.layer.self_attention.attention.causal: True

axlearn/experiments/testdata/axlearn.experiments.text.gpt.c4_trainer/fuji-3B-v3-flash-single-host.txt

@@ -188,7 +188,7 @@ model.decoder.transformer.layer.klass: 'axlearn.common.attention.TransformerLaye
 model.decoder.transformer.layer.remat_spec['prevent_cse']: False
 model.decoder.transformer.layer.remat_spec['policy'].fn: 'axlearn.common.attention._save_and_offload_only_these_names_regex'
 model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_offloaded: None
-model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*([qkvo]_proj|context)'
+model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*[kqv]_proj|.*o_proj|.*context'
 model.decoder.transformer.layer.remat_spec['policy'].offload_dst: 'pinned_host'
 model.decoder.transformer.layer.remat_spec['policy'].offload_src: 'device'
 model.decoder.transformer.layer.self_attention.attention.causal: True

axlearn/experiments/testdata/axlearn.experiments.text.gpt.c4_trainer/fuji-3B-v3-flash.txt

@@ -188,7 +188,7 @@ model.decoder.transformer.layer.klass: 'axlearn.common.attention.TransformerLaye
 model.decoder.transformer.layer.remat_spec['prevent_cse']: False
 model.decoder.transformer.layer.remat_spec['policy'].fn: 'axlearn.common.attention._save_and_offload_only_these_names_regex'
 model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_offloaded: None
-model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*([qkvo]_proj|context)'
+model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*[kqv]_proj|.*o_proj|.*context'
 model.decoder.transformer.layer.remat_spec['policy'].offload_dst: 'pinned_host'
 model.decoder.transformer.layer.remat_spec['policy'].offload_src: 'device'
 model.decoder.transformer.layer.self_attention.attention.causal: True

axlearn/experiments/testdata/axlearn.experiments.text.gpt.c4_trainer/fuji-3B-v3-single-host.txt

@@ -188,7 +188,7 @@ model.decoder.transformer.layer.klass: 'axlearn.common.attention.TransformerLaye
 model.decoder.transformer.layer.remat_spec['prevent_cse']: False
 model.decoder.transformer.layer.remat_spec['policy'].fn: 'axlearn.common.attention._save_and_offload_only_these_names_regex'
 model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_offloaded: None
-model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*([qkvo]_proj|context)'
+model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*[kqv]_proj|.*o_proj|.*context'
 model.decoder.transformer.layer.remat_spec['policy'].offload_dst: 'pinned_host'
 model.decoder.transformer.layer.remat_spec['policy'].offload_src: 'device'
 model.decoder.transformer.layer.self_attention.attention.causal: True

axlearn/experiments/testdata/axlearn.experiments.text.gpt.c4_trainer/fuji-3B-v3.txt

@@ -188,7 +188,7 @@ model.decoder.transformer.layer.klass: 'axlearn.common.attention.TransformerLaye
 model.decoder.transformer.layer.remat_spec['prevent_cse']: False
 model.decoder.transformer.layer.remat_spec['policy'].fn: 'axlearn.common.attention._save_and_offload_only_these_names_regex'
 model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_offloaded: None
-model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*([qkvo]_proj|context)'
+model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*[kqv]_proj|.*o_proj|.*context'
 model.decoder.transformer.layer.remat_spec['policy'].offload_dst: 'pinned_host'
 model.decoder.transformer.layer.remat_spec['policy'].offload_src: 'device'
 model.decoder.transformer.layer.self_attention.attention.causal: True

axlearn/experiments/testdata/axlearn.experiments.text.gpt.c4_trainer/fuji-70B-v1-flash.txt

@@ -135,6 +135,22 @@ mesh_rules[1][1][2]: 1
 mesh_rules[1][1][3]: 128
 mesh_rules[1][1][4]: 1
 mesh_rules[1][1][5]: 1
+mesh_rules[2][0]: 'neuron-(trn2|trn2n).48xlarge-64'
+mesh_rules[2][1].config_modifiers[0].klass: 'axlearn.common.trainer_config_modifier.MeshShapeModifier'
+mesh_rules[2][1].config_modifiers[0].mesh_shape[0]: 1
+mesh_rules[2][1].config_modifiers[0].mesh_shape[1]: 1
+mesh_rules[2][1].config_modifiers[0].mesh_shape[2]: 1
+mesh_rules[2][1].config_modifiers[0].mesh_shape[3]: -1
+mesh_rules[2][1].config_modifiers[0].mesh_shape[4]: 1
+mesh_rules[2][1].config_modifiers[0].mesh_shape[5]: 4
+mesh_rules[2][1].config_modifiers[1].klass: 'axlearn.common.trainer_config_modifier.RematSpecModifier'
+mesh_rules[2][1].config_modifiers[1].remat_policies['model.decoder.transformer.layer']['prevent_cse']: True
+mesh_rules[2][1].config_modifiers[1].remat_policies['model.decoder.transformer.layer']['policy'].fn: 'axlearn.common.attention._save_and_offload_only_these_names_regex'
+mesh_rules[2][1].config_modifiers[1].remat_policies['model.decoder.transformer.layer']['policy'].names_which_can_be_offloaded: None
+mesh_rules[2][1].config_modifiers[1].remat_policies['model.decoder.transformer.layer']['policy'].names_which_can_be_saved: '.*[kqv]_proj|.*linear1_[01]'
+mesh_rules[2][1].config_modifiers[1].remat_policies['model.decoder.transformer.layer']['policy'].offload_dst: None
+mesh_rules[2][1].config_modifiers[1].remat_policies['model.decoder.transformer.layer']['policy'].offload_src: None
+mesh_rules[2][1].klass: 'axlearn.common.trainer_config_modifier.ChainConfigModifier'
 mesh_shape[0]: 1
 mesh_shape[1]: 1
 mesh_shape[2]: 1
@@ -214,7 +230,7 @@ model.decoder.transformer.layer.klass: 'axlearn.common.attention.TransformerLaye
 model.decoder.transformer.layer.remat_spec['prevent_cse']: False
 model.decoder.transformer.layer.remat_spec['policy'].fn: 'axlearn.common.attention._save_and_offload_only_these_names_regex'
 model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_offloaded: None
-model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*([qkvo]_proj|context)'
+model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*[kqv]_proj|.*o_proj|.*context'
 model.decoder.transformer.layer.remat_spec['policy'].offload_dst: 'pinned_host'
 model.decoder.transformer.layer.remat_spec['policy'].offload_src: 'device'
 model.decoder.transformer.layer.self_attention.attention.causal: True

axlearn/experiments/testdata/axlearn.experiments.text.gpt.c4_trainer/fuji-70B-v1.txt

@@ -135,6 +135,22 @@ mesh_rules[1][1][2]: 1
 mesh_rules[1][1][3]: 128
 mesh_rules[1][1][4]: 1
 mesh_rules[1][1][5]: 1
+mesh_rules[2][0]: 'neuron-(trn2|trn2n).48xlarge-64'
+mesh_rules[2][1].config_modifiers[0].klass: 'axlearn.common.trainer_config_modifier.MeshShapeModifier'
+mesh_rules[2][1].config_modifiers[0].mesh_shape[0]: 1
+mesh_rules[2][1].config_modifiers[0].mesh_shape[1]: 1
+mesh_rules[2][1].config_modifiers[0].mesh_shape[2]: 1
+mesh_rules[2][1].config_modifiers[0].mesh_shape[3]: -1
+mesh_rules[2][1].config_modifiers[0].mesh_shape[4]: 1
+mesh_rules[2][1].config_modifiers[0].mesh_shape[5]: 4
+mesh_rules[2][1].config_modifiers[1].klass: 'axlearn.common.trainer_config_modifier.RematSpecModifier'
+mesh_rules[2][1].config_modifiers[1].remat_policies['model.decoder.transformer.layer']['prevent_cse']: True
+mesh_rules[2][1].config_modifiers[1].remat_policies['model.decoder.transformer.layer']['policy'].fn: 'axlearn.common.attention._save_and_offload_only_these_names_regex'
+mesh_rules[2][1].config_modifiers[1].remat_policies['model.decoder.transformer.layer']['policy'].names_which_can_be_offloaded: None
+mesh_rules[2][1].config_modifiers[1].remat_policies['model.decoder.transformer.layer']['policy'].names_which_can_be_saved: '.*[kqv]_proj|.*linear1_[01]'
+mesh_rules[2][1].config_modifiers[1].remat_policies['model.decoder.transformer.layer']['policy'].offload_dst: None
+mesh_rules[2][1].config_modifiers[1].remat_policies['model.decoder.transformer.layer']['policy'].offload_src: None
+mesh_rules[2][1].klass: 'axlearn.common.trainer_config_modifier.ChainConfigModifier'
 mesh_shape[0]: 1
 mesh_shape[1]: 1
 mesh_shape[2]: 1
@@ -214,7 +230,7 @@ model.decoder.transformer.layer.klass: 'axlearn.common.attention.TransformerLaye
 model.decoder.transformer.layer.remat_spec['prevent_cse']: False
 model.decoder.transformer.layer.remat_spec['policy'].fn: 'axlearn.common.attention._save_and_offload_only_these_names_regex'
 model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_offloaded: None
-model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*([qkvo]_proj|context)'
+model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*[kqv]_proj|.*o_proj|.*context'
 model.decoder.transformer.layer.remat_spec['policy'].offload_dst: 'pinned_host'
 model.decoder.transformer.layer.remat_spec['policy'].offload_src: 'device'
 model.decoder.transformer.layer.self_attention.attention.causal: True

axlearn/experiments/testdata/axlearn.experiments.text.gpt.c4_trainer/fuji-70B-v2-flash.txt

@@ -135,6 +135,22 @@ mesh_rules[1][1][2]: 1
 mesh_rules[1][1][3]: 128
 mesh_rules[1][1][4]: 1
 mesh_rules[1][1][5]: 1
+mesh_rules[2][0]: 'neuron-(trn2|trn2n).48xlarge-64'
+mesh_rules[2][1].config_modifiers[0].klass: 'axlearn.common.trainer_config_modifier.MeshShapeModifier'
+mesh_rules[2][1].config_modifiers[0].mesh_shape[0]: 1
+mesh_rules[2][1].config_modifiers[0].mesh_shape[1]: 1
+mesh_rules[2][1].config_modifiers[0].mesh_shape[2]: 1
+mesh_rules[2][1].config_modifiers[0].mesh_shape[3]: -1
+mesh_rules[2][1].config_modifiers[0].mesh_shape[4]: 1
+mesh_rules[2][1].config_modifiers[0].mesh_shape[5]: 4
+mesh_rules[2][1].config_modifiers[1].klass: 'axlearn.common.trainer_config_modifier.RematSpecModifier'
+mesh_rules[2][1].config_modifiers[1].remat_policies['model.decoder.transformer.layer']['prevent_cse']: True
+mesh_rules[2][1].config_modifiers[1].remat_policies['model.decoder.transformer.layer']['policy'].fn: 'axlearn.common.attention._save_and_offload_only_these_names_regex'
+mesh_rules[2][1].config_modifiers[1].remat_policies['model.decoder.transformer.layer']['policy'].names_which_can_be_offloaded: None
+mesh_rules[2][1].config_modifiers[1].remat_policies['model.decoder.transformer.layer']['policy'].names_which_can_be_saved: '.*[kqv]_proj|.*linear1_[01]'
+mesh_rules[2][1].config_modifiers[1].remat_policies['model.decoder.transformer.layer']['policy'].offload_dst: None
+mesh_rules[2][1].config_modifiers[1].remat_policies['model.decoder.transformer.layer']['policy'].offload_src: None
+mesh_rules[2][1].klass: 'axlearn.common.trainer_config_modifier.ChainConfigModifier'
 mesh_shape[0]: 1
 mesh_shape[1]: 1
 mesh_shape[2]: 1
@@ -214,7 +230,7 @@ model.decoder.transformer.layer.klass: 'axlearn.common.attention.TransformerLaye
 model.decoder.transformer.layer.remat_spec['prevent_cse']: False
 model.decoder.transformer.layer.remat_spec['policy'].fn: 'axlearn.common.attention._save_and_offload_only_these_names_regex'
 model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_offloaded: None
-model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*([qkvo]_proj|context)'
+model.decoder.transformer.layer.remat_spec['policy'].names_which_can_be_saved: '.*[kqv]_proj|.*o_proj|.*context'
 model.decoder.transformer.layer.remat_spec['policy'].offload_dst: 'pinned_host'
 model.decoder.transformer.layer.remat_spec['policy'].offload_src: 'device'
 model.decoder.transformer.layer.self_attention.attention.causal: True