lenet2.pbtxt

lenet2.pbtxt

node {
  name: "conv2d_input"
  op: "Placeholder"
  attr {
    key: "dtype"
    value {
      type: DT_FLOAT
    }
  }
  attr {
    key: "shape"
    value {
      shape {
        dim {
          size: -1
        }
        dim {
          size: 40
        }
        dim {
          size: 40
        }
        dim {
          size: 3
        }
      }
    }
  }
}
node {
  name: "conv2d/kernel/read"
  op: "Identity"
  input: "conv2d/kernel"
  attr {
    key: "_class"
    value {
      list {
        s: "loc:@conv2d/kernel"
      }
    }
  }
}
node {
  name: "conv2d/bias/read"
  op: "Identity"
  input: "conv2d/bias"
  attr {
    key: "_class"
    value {
      list {
        s: "loc:@conv2d/bias"
      }
    }
  }
}
node {
  name: "conv2d/convolution"
  op: "Conv2D"
  input: "conv2d_input"
  input: "conv2d/kernel/read"
  attr {
    key: "dilations"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "conv2d/BiasAdd"
  op: "BiasAdd"
  input: "conv2d/convolution"
  input: "conv2d/bias/read"
}
node {
  name: "activation/Relu"
  op: "Relu"
  input: "conv2d/BiasAdd"
}
node {
  name: "max_pooling2d/MaxPool"
  op: "MaxPool"
  input: "activation/Relu"
  attr {
    key: "ksize"
    value {
      list {
        i: 1
        i: 2
        i: 2
        i: 1
      }
    }
  }
  attr {
    key: "padding"
    value {
      s: "VALID"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 2
        i: 2
        i: 1
      }
    }
  }
}
node {
  name: "conv2d_1/kernel/read"
  op: "Identity"
  input: "conv2d_1/kernel"
  attr {
    key: "_class"
    value {
      list {
        s: "loc:@conv2d_1/kernel"
      }
    }
  }
}
node {
  name: "conv2d_1/bias/read"
  op: "Identity"
  input: "conv2d_1/bias"
  attr {
    key: "_class"
    value {
      list {
        s: "loc:@conv2d_1/bias"
      }
    }
  }
}
node {
  name: "conv2d_1/convolution"
  op: "Conv2D"
  input: "max_pooling2d/MaxPool"
  input: "conv2d_1/kernel/read"
  attr {
    key: "dilations"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
  attr {
    key: "padding"
    value {
      s: "SAME"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 1
        i: 1
        i: 1
      }
    }
  }
}
node {
  name: "conv2d_1/BiasAdd"
  op: "BiasAdd"
  input: "conv2d_1/convolution"
  input: "conv2d_1/bias/read"
}
node {
  name: "activation_1/Relu"
  op: "Relu"
  input: "conv2d_1/BiasAdd"
}
node {
  name: "max_pooling2d_1/MaxPool"
  op: "MaxPool"
  input: "activation_1/Relu"
  attr {
    key: "ksize"
    value {
      list {
        i: 1
        i: 2
        i: 2
        i: 1
      }
    }
  }
  attr {
    key: "padding"
    value {
      s: "VALID"
    }
  }
  attr {
    key: "strides"
    value {
      list {
        i: 1
        i: 2
        i: 2
        i: 1
      }
    }
  }
}
node {
  name: "flatten/Shape"
  op: "Flatten"
  input: "max_pooling2d_1/MaxPool"
  attr {
    key: "out_type"
    value {
      type: DT_INT32
    }
  }
}
node {
  name: "dense/kernel/read"
  op: "Identity"
  input: "dense/kernel"
  attr {
    key: "_class"
    value {
      list {
        s: "loc:@dense/kernel"
      }
    }
  }
}
node {
  name: "dense/bias/read"
  op: "Identity"
  input: "dense/bias"
  attr {
    key: "_class"
    value {
      list {
        s: "loc:@dense/bias"
      }
    }
  }
}
node {
  name: "dense/MatMul"
  op: "MatMul"
  input: "flatten/Shape"
  input: "dense/kernel/read"
  attr {
    key: "transpose_a"
    value {
      b: false
    }
  }
  attr {
    key: "transpose_b"
    value {
      b: false
    }
  }
}
node {
  name: "dense/BiasAdd"
  op: "BiasAdd"
  input: "dense/MatMul"
  input: "dense/bias/read"
}
node {
  name: "activation_2/Relu"
  op: "Relu"
  input: "dense/BiasAdd"
}
node {
  name: "dense_1/kernel/read"
  op: "Identity"
  input: "dense_1/kernel"
  attr {
    key: "_class"
    value {
      list {
        s: "loc:@dense_1/kernel"
      }
    }
  }
}
node {
  name: "dense_1/bias/read"
  op: "Identity"
  input: "dense_1/bias"
  attr {
    key: "_class"
    value {
      list {
        s: "loc:@dense_1/bias"
      }
    }
  }
}
node {
  name: "dense_1/MatMul"
  op: "MatMul"
  input: "activation_2/Relu"
  input: "dense_1/kernel/read"
  attr {
    key: "transpose_a"
    value {
      b: false
    }
  }
  attr {
    key: "transpose_b"
    value {
      b: false
    }
  }
}
node {
  name: "dense_1/BiasAdd"
  op: "BiasAdd"
  input: "dense_1/MatMul"
  input: "dense_1/bias/read"
}
node {
  name: "activation_3/Softmax"
  op: "Softmax"
  input: "dense_1/BiasAdd"
}
library {
}

hello, I don't know how manually replace all flatten nodes with a single Flatten?

@xzy-666 - sorry, i cannot help you

@xzy-666 - sorry, i cannot help you

how do you get the pbtxt?

sorry again, i have no idea, how this got here, or the context it was used in