add code

mindspore-jina/MindsporeLeNet/requirements.txt

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+jina

mindspore-jina/__init__.py

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-import numpy as np
-from jina.executors.encoders.frameworks import BaseMindsporeEncoder
-
-
-class MindsporeLeNet(BaseMindsporeEncoder):
-    """
-    :class:`MindsporeLeNet` Encoding image into vectors using mindspore.
-    """
-
-    def encode(self, data, *args, **kwargs):
-        # data is B x D, where D = 28 * 28
-        # LeNet only accepts BCHW format where H=W=32
-        # hence we need to do some simple transform
-        from mindspore import Tensor
-
-        data = np.pad(data.reshape([-1, 1, 28, 28]),
-                      [(0, 0), (0, 0), (0, 4), (0, 4)]).astype('float32')
-        return self.model(Tensor(data)).asnumpy()
-
-    def get_cell(self):
-        from .lenet.src.lenet import LeNet5
-        class LeNet5Embed(LeNet5):
-            def construct(self, x):
-                x = self.conv1(x)
-                x = self.relu(x)
-                x = self.max_pool2d(x)
-                x = self.conv2(x)
-                x = self.relu(x)
-                x = self.max_pool2d(x)
-                x = self.flatten(x)
-                x = self.fc1(x)
-                x = self.relu(x)
-                x = self.fc2(x)
-                x = self.relu(x)
-                return x
-
-        return LeNet5Embed()