[Ospp] VisualDL Support Paddle PIR (#1279)

* VisualDL Adaptation for Paddle PIR

* [Doc] Add document for VisualDL Adaptation for Paddle PIR

* Dynamic graph changemodel interfaces support *.json file

* [Doc] Add document for VisualDL Adaptation for Paddle PIR

* [Doc] Add document for VisualDL Adaptation for Paddle PIR

* Update Paddle PIR Visualization.md

* Fix code style

* Fix paddle dependency

demo/components/cond_inside_cond_test.py

@@ -0,0 +1,69 @@
+# Copyright (c) 2024 VisualDL Authors. All Rights Reserve.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# =======================================================================
+import paddle
+from visualdl import LogWriter
+"""
+        pseudocode:
+        for i in range(1, 10):
+            a = 2 * i
+            if i < 5:
+                if i >= 3:
+                    return a + a
+                else:
+                    return a - a
+            else:
+                if i < 8:
+                    return a * a
+                else:
+                    return a / a
+"""
+paddle.enable_static()
+
+
+def less_than_branch(i, a):
+    return paddle.static.nn.cond(
+        i >= 3.0,
+        lambda: paddle.add(a, a),
+        lambda: paddle.subtract(a, a),
+    )
+
+
+def greater_equal_branch(i, a):
+    return paddle.static.nn.cond(
+        i < 8.0,
+        lambda: paddle.multiply(a, a),
+        lambda: paddle.divide(a, a),
+    )
+
+
+main_program = paddle.static.Program()
+startup_program = paddle.static.Program()
+with paddle.static.program_guard(main_program, startup_program):
+    i = paddle.static.data(name="i", shape=[1], dtype='float32')
+    i.stop_gradient = False
+    a = 2.0 * i
+    out = paddle.static.nn.cond(
+        i < 5.0,
+        lambda: less_than_branch(i, a),
+        lambda: greater_equal_branch(i, a),
+    )
+    mean = paddle.mean(out)
+
+with LogWriter(logdir="./log/cond_inside_cond_test/") as writer:
+    writer.add_graph(
+        model=main_program,
+        input_spec=[paddle.static.InputSpec([1], dtype='float32')],
+        verbose=True,
+        is_pir=True)

demo/components/cond_test.py

@@ -0,0 +1,62 @@
+# Copyright (c) 2024 VisualDL Authors. All Rights Reserve.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# =======================================================================
+import paddle
+from visualdl import LogWriter
+
+paddle.enable_static()
+"""
+    pseudocode:
+    for i in range(1, 10):
+        a = 2 * i
+        if i < 5:
+            return a + a
+        else:
+            return a - a
+"""
+
+
+class ConditionalLayer(paddle.nn.Layer):
+    def __init__(self):
+        super(ConditionalLayer, self).__init__()
+
+    def forward(self, i):
+        a = 2.0 * i
+        out = paddle.static.nn.cond(
+            i < 5.0,
+            lambda: paddle.add(a, a),
+            lambda: paddle.subtract(a, a),
+        )
+        return out
+
+
+main_program = paddle.static.Program()
+startup_program = paddle.static.Program()
+with paddle.static.program_guard(main_program, startup_program):
+    i = paddle.static.data(name="i", shape=[1], dtype='float32')
+    i.stop_gradient = False
+    a = 2.0 * i
+    out = paddle.static.nn.cond(
+        i < 5.0,
+        lambda: paddle.add(a, a),
+        lambda: paddle.subtract(a, a),
+    )
+    mean = paddle.mean(out)
+
+with LogWriter(logdir="./log/cond_test/") as writer:
+    writer.add_graph(
+        model=main_program,
+        input_spec=[paddle.static.InputSpec([1], 'float32')],
+        verbose=True,
+        is_pir=True)

demo/components/pir_graph_test.py

@@ -0,0 +1,54 @@
+# Copyright (c) 2024 VisualDL Authors. All Rights Reserve.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# =======================================================================
+import paddle
+import paddle.nn.functional as F
+from paddle import nn
+from visualdl import LogWriter
+
+
+class MyNet(nn.Layer):
+    def __init__(self):
+        super(MyNet, self).__init__()
+        self.conv1 = nn.Conv2D(
+            in_channels=1, out_channels=20, kernel_size=5, stride=1, padding=2)
+        self.max_pool1 = nn.MaxPool2D(kernel_size=2, stride=2)
+        self.conv2 = nn.Conv2D(
+            in_channels=20,
+            out_channels=20,
+            kernel_size=5,
+            stride=1,
+            padding=2)
+        self.max_pool2 = nn.MaxPool2D(kernel_size=2, stride=2)
+        self.fc = nn.Linear(in_features=980, out_features=10)
+
+    def forward(self, inputs):
+        x = self.conv1(inputs)
+        x = F.relu(x)
+        x = self.max_pool1(x)
+        x = self.conv2(x)
+        x = F.relu(x)
+        x = self.max_pool2(x)
+        x = paddle.reshape(x, [x.shape[0], -1])
+        x = self.fc(x)
+        return x
+
+
+net = MyNet()
+with LogWriter(logdir="./log/pir_graph_test/") as writer:
+    writer.add_graph(
+        model=net,
+        input_spec=[paddle.static.InputSpec([-1, 1, 28, 28], 'float32')],
+        verbose=True,
+        is_pir=True)

demo/components/pir_translate.py → demo/components/pir_program_test.py

@@ -1,6 +1,18 @@
+# Copyright (c) 2024 VisualDL Authors. All Rights Reserve.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# =======================================================================
 import paddle
-from paddle import ir
-
 from visualdl import LogWriter
 
 paddle.enable_static()
@@ -18,11 +30,9 @@
     batch_norm = paddle.nn.BatchNorm(32, act='relu', data_layout='NHWC')
     out = batch_norm(conv2d(tanh_out))
 
-newir_program = ir.translate_to_new_ir(main_program.desc)
-
 with LogWriter(logdir="./log/program_test/") as writer:
     writer.add_graph(
-        model=newir_program,
+        model=main_program,
         input_spec=[paddle.static.InputSpec([-1, 1, 28, 28], 'float32')],
         verbose=True,
         is_pir=True)

demo/components/while_test.py

@@ -0,0 +1,49 @@
+# Copyright (c) 2024 VisualDL Authors. All Rights Reserve.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# =======================================================================
+import paddle
+from visualdl import LogWriter
+
+paddle.enable_static()
+main_program = paddle.static.Program()
+startup_program = paddle.static.Program()
+with paddle.static.program_guard(main_program, startup_program):
+    linear = paddle.nn.Linear(16, 10)
+
+    def cond(i, loop_len, x, result):
+        return i < loop_len
+
+    def body(i, loop_len, x, result):
+        result = linear(x)
+        paddle.increment(i)
+        return [i, loop_len, x, result]
+
+    x = paddle.static.data(name='x', shape=[32, 16], dtype='float32')
+    i = paddle.zeros(shape=[1], dtype='int64')
+    loop_len = paddle.ones(shape=[1], dtype='int64')
+    result = paddle.zeros(
+        shape=x.shape[:-1] + linear.weight.shape[-1:], dtype="float32"
+    )
+    result.stop_gradient = False
+    _, _, _, results = paddle.static.nn.while_loop(
+        cond, body, [i, loop_len, x, result]
+    )
+    loss = paddle.mean(results)
+
+with LogWriter(logdir="./log/while_test/") as writer:
+    writer.add_graph(
+        model=main_program,
+        input_spec=[paddle.static.InputSpec([1], 'float32')],
+        verbose=True,
+        is_pir=True)