nonstopfor opened a new issue #6990:
URL: https://github.com/apache/tvm/issues/6990
I am new to TVM and I want to use back propagation to train a simple mlp
model. I find that gradient pass could help me compute the gradient for
different parameters, which could help me train. However, when I try to build,
a problem occurs. Below are the code and the error message.
```
from numpy.core import function_base
import tvm
from tvm import relay
from tvm.relay import GlobalVar
from tvm.relay.op.nn.nn import batch_flatten
from tvm.relay.op.tensor import cos
from tvm.relay.testing import run_infer_type
from tvm.relay import create_executor, transform
from tvm.relay.transform import gradient, PartialEvaluate,
DeadCodeElimination
from tvm.relay.testing import run_infer_type, rand, check_grad,
create_workload
import numpy as np
from tvm.relay.transform.transform import ForwardFoldScaleAxis
from tvm.contrib import graph_runtime as runtime
def normal_mlp(data_shape, label_shape):
data = relay.var("data", shape=data_shape, dtype="float32")
label = relay.var("data", shape=label_shape, dtype="float32")
fc1 = relay.nn.dense(data, relay.var("fc1_weight"), units=128)
fc1 = relay.nn.bias_add(fc1, relay.var("fc1_bias"), axis=-1)
act1 = relay.nn.relu(fc1)
fc2 = relay.nn.dense(act1, relay.var("fc2_weight"), units=64)
fc2 = relay.nn.bias_add(fc2, relay.var("fc2_bias"), axis=-1)
act2 = relay.nn.relu(fc2)
fc3 = relay.nn.dense(act2, relay.var("fc3_weight"), units=10)
fc3 = relay.nn.bias_add(fc3, relay.var("fc3_bias"), axis=-1)
mlp = relay.nn.softmax(data=fc3)
mlp = relay.nn.cross_entropy(mlp, label)
args = relay.analysis.free_vars(mlp)
return relay.Function(args, mlp)
data_shape = (batch_size, 784)
label_shape = (batch_size, 10)
valid_shape = (100, 784)
dtype = "float32"
func = normal_mlp(data_shape, label_shape)
func = run_infer_type(func)
back = run_infer_type(gradient(func))
mod, params = create_workload(back)
opt_level = 0
with tvm.transform.PassContext(opt_level=opt_level):
lib = relay.build(mod, target='llvm', params=params)
```
The error message is:
`Traceback (most recent call last): File “build_test.py”, line 165, in
mlp_training() File “build_test.py”, line 113, in mlp_training lib =
relay.build(mod, target=‘llvm’, params=params) File
“/home/zzx/tvm/python/tvm/relay/build_module.py”, line 260, in build
graph_json, mod, params = bld_mod.build(mod, target, target_host, params) File
“/home/zzx/tvm/python/tvm/relay/build_module.py”, line 127, in build
self._build(mod, target, target_host) File
“/home/zzx/tvm/python/tvm/_ffi/_ctypes/packed_func.py”, line 237, in call raise
get_last_ffi_error() tvm._ffi.base.TVMError: Traceback (most recent call last):
[bt] (8)
/home/zzx/tvm/build/libtvm.so(tvm::relay::backend::GraphRuntimeCodegen::Codegen(tvm::relay::Function)+0x118)
[0x7f85bda6f6b8] [bt] (7)
/home/zzx/tvm/build/libtvm.so(std::_Function_handler<void
(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*),
tvm::runtime::TypedPackedFunc<tvm::Map<tvm::RelayExpr,
tvm::runtime::Array<tvm::runtime::Array<tvm::Inte
ger, void>, void>, void, void> (tvm::relay::Function
const&)>::AssignTypedLambda<tvm::Map<tvm::RelayExpr,
tvm::runtime::Array<tvm::runtime::Array<tvm::Integer, void>, void>, void, void>
()(tvm::relay::Function const&)>(tvm::Map<tvm::RelayExpr,
tvm::runtime::Array<tvm::runtime::Array<tvm::Integer, void>, void>, void, void>
()(tvm::relay::Function const&))::{lambda(tvm::runtime::TVMArgs const&,
tvm::runtime::TVMRetValue*)#1}>::M_invoke(std::Any_data const&,
tvm::runtime::TVMArgs&&, tvm::runtime::TVMRetValue*&&)+0x124) [0x7f85bda53794]
[bt] (6)
/home/zzx/tvm/build/libtvm.so(tvm::relay::GraphPlanMemory(tvm::relay::Function
const&)+0x183) [0x7f85bda4a9b3] [bt] (5)
/home/zzx/tvm/build/libtvm.so(tvm::relay::StorageAllocator::Plan(tvm::relay::Function
const&)+0x293) [0x7f85bda500c3] [bt] (4)
/home/zzx/tvm/build/libtvm.so(tvm::relay::StorageAllocaBaseVisitor::GetToken(tvm::RelayExpr
const&)+0x16) [0x7f85bda4b786] [bt] (3)
/home/zzx/tvm/build/libtvm.so(tvm::relay::ExprVisitor::VisitExpr(tvm::
RelayExpr const&)+0x8b) [0x7f85bdaf2fab] [bt] (2)
/home/zzx/tvm/build/libtvm.so(tvm::relay::ExprFunctor<void (tvm::RelayExpr
const&)>::VisitExpr(tvm::RelayExpr const&)+0x6f) [0x7f85bdaa3aff] [bt] (1)
/home/zzx/tvm/build/libtvm.so(tvm::relay::StorageAllocaBaseVisitor::VisitExpr(tvm::relay::LetNode
const*)+0x2be) [0x7f85bda52cfe] [bt] (0)
/home/zzx/tvm/build/libtvm.so(+0x113a7d8) [0x7f85bda4a7d8] File
“/home/zzx/tvm/src/relay/backend/graph_plan_memory.cc”, line 118 TVMError:
Check failed: it != token_map.end():`
Does anybody know how to solve this problem?
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