From 99d466a1a6cdafe6321f9dfc380070abc872cf43 Mon Sep 17 00:00:00 2001
From: tangwei <tangwei12@baidu.com>
Date: Thu, 11 Jun 2020 14:40:21 +0800
Subject: [PATCH] fix windows adapter

---
 core/model.py                      | 29 +++--------------------------
 core/trainers/framework/network.py | 14 ++++++++++----
 core/trainers/framework/runner.py  |  2 +-
 core/utils/envs.py                 |  5 +++++
 4 files changed, 19 insertions(+), 31 deletions(-)

diff --git a/core/model.py b/core/model.py
index e39573c2..bb2040e4 100755
--- a/core/model.py
+++ b/core/model.py
@@ -88,7 +88,7 @@ class ModelBase(object):
                 self._data_var.append(l)
                 self._sparse_data_var.append(l)
 
-        dataset_class = dataset["type"]
+        dataset_class = envs.get_global_env(name + "type")
         if dataset_class == "DataLoader":
             self._init_dataloader()
 
@@ -204,31 +204,8 @@ class ModelBase(object):
     def net(self, is_infer=False):
         return None
 
-    def _construct_reader(self, is_infer=False):
-        if is_infer:
-            self._infer_data_loader = fluid.io.DataLoader.from_generator(
-                feed_list=self._infer_data_var,
-                capacity=64,
-                use_double_buffer=False,
-                iterable=False)
-        else:
-            dataset_class = envs.get_global_env("dataset_class", None,
-                                                "train.reader")
-            if dataset_class == "DataLoader":
-                self._data_loader = fluid.io.DataLoader.from_generator(
-                    feed_list=self._data_var,
-                    capacity=64,
-                    use_double_buffer=False,
-                    iterable=False)
-
     def train_net(self):
-        input_data = self.input_data(is_infer=False)
-        self._data_var = input_data
-        self._construct_reader(is_infer=False)
-        self.net(input_data, is_infer=False)
+        pass
 
     def infer_net(self):
-        input_data = self.input_data(is_infer=True)
-        self._infer_data_var = input_data
-        self._construct_reader(is_infer=True)
-        self.net(input_data, is_infer=True)
+        pass
diff --git a/core/trainers/framework/network.py b/core/trainers/framework/network.py
index 7d1e276e..71f2a4e7 100644
--- a/core/trainers/framework/network.py
+++ b/core/trainers/framework/network.py
@@ -97,7 +97,8 @@ class SingleNetwork(NetworkBase):
 
         context["dataset"] = {}
         for dataset in context["env"]["dataset"]:
-            if dataset["type"] != "DataLoader":
+            type = envs.get_global_env("dataset." + dataset["name"] + ".type")
+            if type != "DataLoader":
                 dataset_class = QueueDataset(context)
                 context["dataset"][dataset[
                     "name"]] = dataset_class.create_dataset(dataset["name"],
@@ -155,7 +156,9 @@ class PSNetwork(NetworkBase):
             context["fleet"].init_worker()
             context["dataset"] = {}
             for dataset in context["env"]["dataset"]:
-                if dataset["type"] != "DataLoader":
+                type = envs.get_global_env("dataset." + dataset["name"] +
+                                           ".type")
+                if type != "DataLoader":
                     dataset_class = QueueDataset(context)
                     context["dataset"][dataset[
                         "name"]] = dataset_class.create_dataset(
@@ -248,7 +251,9 @@ class PslibNetwork(NetworkBase):
         else:
             context["dataset"] = {}
             for dataset in context["env"]["dataset"]:
-                if dataset["type"] != "DataLoader":
+                type = envs.get_global_env("dataset." + dataset["name"] +
+                                           ".type")
+                if type != "DataLoader":
                     dataset_class = QueueDataset(context)
                     context["dataset"][dataset[
                         "name"]] = dataset_class.create_dataset(
@@ -312,7 +317,8 @@ class CollectiveNetwork(NetworkBase):
 
         context["dataset"] = {}
         for dataset in context["env"]["dataset"]:
-            if dataset["type"] != "DataLoader":
+            type = envs.get_global_env("dataset." + dataset["name"] + ".type")
+            if type != "DataLoader":
                 dataset_class = QueueDataset(context)
                 context["dataset"][dataset[
                     "name"]] = dataset_class.create_dataset(dataset["name"],
diff --git a/core/trainers/framework/runner.py b/core/trainers/framework/runner.py
index 7c61c412..52be3e00 100644
--- a/core/trainers/framework/runner.py
+++ b/core/trainers/framework/runner.py
@@ -155,7 +155,7 @@ class RunnerBase(object):
             gradient_scale_strategy = fluid.BuildStrategy.GradientScaleStrategy.Customized
         else:
             raise ValueError(
-                "Unsurpported config. gradient_scale_strategy must be one of [0, 1, 2]."
+                "Unsupported config. gradient_scale_strategy must be one of [0, 1, 2]."
             )
         _build_strategy.gradient_scale_strategy = gradient_scale_strategy
 
diff --git a/core/utils/envs.py b/core/utils/envs.py
index 98bc6a8c..f70db966 100755
--- a/core/utils/envs.py
+++ b/core/utils/envs.py
@@ -96,6 +96,11 @@ def set_global_envs(envs):
             value = os_path_adapter(workspace_adapter(value))
             global_envs[name] = value
 
+    if get_platform() != "LINUX":
+        for dataset in envs["dataset"]:
+            name = ".".join("dataset", dataset["name"], "type")
+            global_envs[name] = "DataLoader"
+
 
 def get_global_env(env_name, default_value=None, namespace=None):
     """
-- 
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