Merge branch 'develop' into add_albert_model

Author: RbRe145

graph_net/test/nlp_model_getter.py

@@ -243,4 +243,4 @@ 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/PaddleX/Cascade-FasterRCNN-ResNet50-FPN/subgraph_0/graph_hash.txt

@@ -0,0 +1 @@
+ef1cff7d6a09085f5a39414177fefe578d79f40af14d0cf5f79e9d5fbd2cd740

paddle_samples/PaddleX/Cascade-FasterRCNN-ResNet50-FPN/subgraph_0/graph_net.json

@@ -0,0 +1,6 @@
+{
+    "framework": "paddle",
+    "model_name": "Cascade-FasterRCNN-ResNet50-FPN",
+    "num_devices_required": 1,
+    "num_nodes_required": 1
+}

paddle_samples/PaddleX/Cascade-FasterRCNN-ResNet50-FPN/subgraph_0/input_meta.py

@@ -0,0 +1,53 @@
+class Program_weight_tensor_data_0:
+    name = "data_0"
+    shape = []
+    dtype = "int64"
+    data = [3]
+
+
+class Program_weight_tensor_data_1:
+    name = "data_1"
+    shape = [512]
+    dtype = "int64"
+    min_val = 0
+    max_val = 511
+    data = None
+
+
+class Program_weight_tensor_data_2:
+    name = "data_2"
+    shape = [512, 4]
+    dtype = "float32"
+    max_val = float("1023.9")
+    mean = float("564.285")
+    std = float("272.403")
+    data = None
+
+
+class Program_weight_tensor_data_3:
+    name = "data_3"
+    shape = [512]
+    dtype = "int64"
+    min_val = 0
+    max_val = 2
+    data = None
+
+
+class Program_weight_tensor_data_4:
+    name = "data_4"
+    shape = [3, 4]
+    dtype = "float32"
+    data = [
+        399.36,
+        483.84,
+        458.24,
+        542.72,
+        680.96,
+        599.04,
+        747.52,
+        668.16,
+        642.56,
+        606.72,
+        688.64,
+        727.04,
+    ]

paddle_samples/PaddleX/Cascade-FasterRCNN-ResNet50-FPN/subgraph_0/model.py

@@ -0,0 +1,47 @@
+import paddle
+
+
+class GraphModule(paddle.nn.Layer):
+    def __init__(self):
+        super().__init__()
+
+    def forward(self, data_0, data_1, data_2, data_3, data_4):
+        # pd_op.full: (xi64) <- ()
+        full_0 = paddle._C_ops.full(
+            [], float("0"), paddle.int64, paddle.framework._current_expected_place()
+        )
+
+        # pd_op.greater_than: (xb) <- (xi64, xi64)
+        greater_than_0 = paddle._C_ops.greater_than(data_0, full_0)
+        del data_0
+
+        # pd_op.cast: (xi64) <- (xb)
+        cast_0 = paddle._C_ops.cast(greater_than_0, paddle.int64)
+        del greater_than_0
+
+        # pd_op.not_equal: (xb) <- (xi64, xi64)
+        not_equal_0 = paddle._C_ops.not_equal(cast_0, full_0)
+        del cast_0
+
+        # pd_op.cast: (xi64) <- (xb)
+        cast_1 = paddle._C_ops.cast(not_equal_0, paddle.int64)
+        del not_equal_0
+
+        # pd_op.equal: (xb) <- (xi64, xi64)
+        equal_0 = paddle._C_ops.equal(cast_1, full_0)
+        del cast_1, full_0
+
+        # pd_op.full: (1xi32) <- ()
+        full_1 = paddle._C_ops.full(
+            [1], float("0"), paddle.int32, paddle.core.CPUPlace()
+        )
+
+        # pd_op.gather: (-1x4xf32) <- (-1x4xf32, -1xi64, 1xi32)
+        gather_0 = paddle._C_ops.gather(data_4, data_3, full_1)
+        del data_3, data_4, full_1
+
+        # pd_op.shape64: (1xi64) <- (512xi64)
+        shape64_0 = paddle._C_ops.shape64(data_1)
+        del data_1
+
+        return gather_0, shape64_0

paddle_samples/PaddleX/PP-DocLayout-M/subgraph_11/weight_meta.py renamed to paddle_samples/PaddleX/Cascade-FasterRCNN-ResNet50-FPN/subgraph_0/weight_meta.py

@@ -0,0 +1 @@
+d84efc51ae2a7d78f2c99b1540a638f4add520ed84de5d62907935b05a8cf292

paddle_samples/PaddleX/Cascade-FasterRCNN-ResNet50-FPN/subgraph_1/graph_hash.txt

@@ -0,0 +1,6 @@
+{
+    "framework": "paddle",
+    "model_name": "Cascade-FasterRCNN-ResNet50-FPN",
+    "num_devices_required": 1,
+    "num_nodes_required": 1
+}

paddle_samples/PaddleX/Cascade-FasterRCNN-ResNet50-FPN/subgraph_1/graph_net.json

@@ -0,0 +1,38 @@
+class Program_weight_tensor_data_0:
+    name = "data_0"
+    shape = [512, 4]
+    dtype = "float32"
+    max_val = float("1018.05")
+    mean = float("439.025")
+    std = float("231.686")
+    data = None
+
+
+class Program_weight_tensor_data_1:
+    name = "data_1"
+    shape = [512, 4]
+    dtype = "float32"
+    max_val = float("938.986")
+    mean = float("467.502")
+    std = float("224.196")
+    data = None
+
+
+class Program_weight_tensor_data_2:
+    name = "data_2"
+    shape = [512, 4]
+    dtype = "float32"
+    max_val = float("936.918")
+    mean = float("499.308")
+    std = float("203.062")
+    data = None
+
+
+class Program_weight_tensor_data_3:
+    name = "data_3"
+    shape = [512, 4]
+    dtype = "float32"
+    max_val = float("981.0")
+    mean = float("506.296")
+    std = float("288.897")
+    data = None