sandeep-krishnamurthy edited a comment on issue #11849: gluon.SymbolBlock cannot imports resnet trained with dtype="float16" URL: https://github.com/apache/incubator-mxnet/issues/11849#issuecomment-417124700 Using below snippet: ``` import mxnet as mx ctx = mx.cpu(0) data = mx.nd.zeros((1,3,224,224), ctx=ctx, dtype='float64') net_fp32 = mx.gluon.model_zoo.vision.resnet34_v2(pretrained=True, ctx=ctx) net_fp32.cast('float64') net_fp32.hybridize() pred = net_fp32.forward(data) net_fp32.export('resnet34_fp16', 0) print('export fp16 model') sm = mx.sym.load('resnet34_fp16-symbol.json') inputs = mx.sym.var('data', dtype='float64') net_fp16 = mx.gluon.SymbolBlock(sm, inputs) net_fp16.collect_params().load('resnet34_fp16-0000.params', ctx) pred = net_fp16.forward(data) ``` Below are my findings: 1. Casting worked fine. 2. Saved parameters are in the correct format (fp64 in my sample code) 3. sym.load worked fine. If I infer symbol's type (sym.infer_type(data='float64') I get correct inferred type (float64) for all params. Below is the issue: 1. When you create mx.gluon.SymbolBlock(sm, input). It creates the parameters in the Block. Type is not passed for creating the parameter. See here - https://github.com/apache/incubator-mxnet/blob/master/python/mxnet/gluon/block.py#L1058 and the behavior is "If there is not parameter to get, it creates one and uses default type (fp32) https://github.com/apache/incubator-mxnet/blob/master/python/mxnet/gluon/parameter.py#L688 I am working on the fix. @apeforest @ThomasDelteil - FYI
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