Merge branch 'develop' into add_albert_t5

Author: RbRe145

graph_net/test/nlp_model_getter.py

@@ -156,6 +156,7 @@ def get_xlnet_model_and_inputs(model_name, text, dtype):
     return model, enc
 
 
+
 def get_t5_model_and_inputs(model_name, text, dtype):
     import paddle
     from paddlenlp.transformers import T5ForConditionalGeneration, T5Tokenizer
@@ -241,4 +242,4 @@ def get_albert_model_and_inputs(model_name, text, dtype):
         input_ids = enc["input_ids"]
         enc["attention_mask"] = (input_ids != tokenizer.pad_token_id).astype("int64")
 
-    return model, enc
+    return model, enc

graph_net/test_compiler_util.py

@@ -0,0 +1,39 @@
+import os
+
+
+def tolerance_generator(t):
+    # for float16
+    yield 10 ** (t * 3 / 5), 10**t
+    # for bfloat16
+    yield 10 ** (t * 1.796 / 5), 10**t
+    # yield float32
+    yield 10 ** (t * 5.886 / 5), 10**t
+    # yield float64
+    yield 10 ** (t * 7 / 5), 10 ** (t * 7 / 5)
+
+
+def calculate_tolerance_pair(begin, end):
+    tolerance_pair_list = []
+    for t in range(begin, end + 1):
+        for rtol, atol in tolerance_generator(t):
+            effective_atol = float(f"{atol:.3g}")
+            effective_rtol = float(f"{rtol:.3g}")
+            tolerance_pair_list.append(
+                {
+                    "atol": effective_atol,
+                    "rtol": effective_rtol,
+                }
+            )
+    return tolerance_pair_list
+
+
+def generate_allclose_configs(cmp_all_close_func):
+    tolerance_pair_list = calculate_tolerance_pair(-10, 5)
+
+    cmp_configs = []
+    for pair in tolerance_pair_list:
+        atol, rtol = pair["atol"], pair["rtol"]
+        cmp_configs.append(
+            (f"[all_close_atol_{atol:.2E}_rtol_{rtol:.2E}]", cmp_all_close_func, pair)
+        )
+    return cmp_configs

paddle_samples/PaddleNLP/bart-base/graph_hash.txt

@@ -0,0 +1 @@
+752fd67d12054cfd32677bec5eae6b293b7af30f784daf6da7b29049d300361c

paddle_samples/PaddleNLP/chinese-xlnet-base/graph_hash.txt

@@ -0,0 +1 @@
+be19706eab62425b7014788a90447aa1413bb2990334a60dad10a424ce300a9a

paddle_samples/PaddleNLP/chinese-xlnet-large/graph_hash.txt

@@ -0,0 +1 @@
+845a39a2df9046b5673fad1785a3a216037950eb451d58aa167b8b989334fd55

paddle_samples/PaddleNLP/chinese-xlnet-mid/graph_hash.txt

@@ -0,0 +1 @@
+e29ad28c026c0c6760a73db8bfa502afcc3f239b12ca8c2dd3ba3b258544b744

paddle_samples/PaddleNLP/electra-base/graph_hash.txt

@@ -0,0 +1 @@
+03434c5692eadd4f05bb5feaf8ea4eb6778381fda71507383df7c9a01e702062

paddle_samples/PaddleNLP/electra-base/graph_net.json

@@ -0,0 +1,6 @@
+{
+    "framework": "paddle",
+    "model_name": "electra-base",
+    "num_devices_required": 1,
+    "num_nodes_required": 1
+}

paddle_samples/PaddleNLP/electra-base/input_meta.py

@@ -0,0 +1,34 @@
+class Program_weight_tensor_data_0:
+    name = "data_0"
+    shape = [1, 21]
+    dtype = "int64"
+    data = [
+        101,
+        7592,
+        1010,
+        2026,
+        2171,
+        2003,
+        3960,
+        1012,
+        1045,
+        2572,
+        4083,
+        2055,
+        2312,
+        2653,
+        4275,
+        1998,
+        2037,
+        4294,
+        2015,
+        1012,
+        102,
+    ]
+
+
+class Program_weight_tensor_data_1:
+    name = "data_1"
+    shape = [1, 21]
+    dtype = "int64"
+    data = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]