python/tvm/relay/frontend/pytorch.py (5 lines):
	- line 129: # TODO (t-vi): handle non-int constants? (like numpy.intXX)
	- line 347: # TODO (t-vi): why is the cast to int needed? similarly elsewhere
	- line 1976: # TODO (t-vi): should this also be part of the type promotion?
	- line 2117: # TODO (yongwww): add new op to avoid the squeeze overhead
	- line 3105: # TODO: scalar inputs


python/tvm/relay/frontend/tflite.py (2 lines):
	- line 754: # TODO - Naive softmax int8 implementation leads to bad accuracy. Currently, we can
	- line 1860: # TODO: Change the output shape calculation based on keep_dim option


rust/tvm-rt/src/map.rs (2 lines):
	- line 234: // TODO: type check
	- line 251: // TODO: type check


python/tvm/driver/tvmc/runner.py (2 lines):
	- line 50: # TODO --device needs to be extended and tested to support other targets,
	- line 388: # TODO expand to other supported devices, as listed in tvm.rpc.client (@leandron)


rust/tvm-graph-rt/src/graph.rs (2 lines):
	- line 327: // TODO: consider `new_with_params` to avoid ever allocating
	- line 332: // FIXME: for no-copy, need setup_op_execs to not capture tensor ptr


python/tvm/topi/arm_cpu/cortex_m7/conv2d/direct.py (2 lines):
	- line 71: # TODO should we add a max_factor attr to these splits?
	- line 177: # TODO add more schedule opts (similar to the NHWC template)


python/tvm/driver/tvmc/compiler.py (2 lines):
	- line 107: # TODO (@leandron) This is a path to a physical file, but
	- line 280: # TODO lib.get_source call have inconsistent behavior for unsupported


vta/tutorials/autotvm/tune_relay_vta.py (1 line):
	- line 219: # check_correctness=True, # TODO: re-enable when check_correctness works again.


python/tvm/relay/frontend/tensorflow_parser.py (1 line):
	- line 160: """TODO: Load checkpoint model."""


python/tvm/script/diagnostics.py (1 line):
	- line 51: self.diag_ctx.render()  # Raise exception on the first error we hit. TODO remove


python/tvm/relay/frontend/onnx.py (1 line):
	- line 2570: # TODO (jwfromm) Test with strided slice once type unifier for this case is fixed.


python/tvm/relay/frontend/tensorflow2.py (1 line):
	- line 562: # TODO: unify prelude and main IRModules


python/tvm/topi/x86/bitserial_dense.py (1 line):
	- line 32: """Bitserial dense implementation. TODO: Why are these separate


src/arith/domain_touched.cc (1 line):
	- line 66: /* TODO: Thread extent unitest not generated.*/


python/tvm/te/hybrid/parser.py (1 line):
	- line 324: # TODO: support defined intermediate buffer later


src/relay/qnn/op/add.cc (1 line):
	- line 48: // FIXME (anijain2305) - The lowering can be further optimized. Instead of inserting requantize in


python/tvm/topi/cuda/dense_tensorcore.py (1 line):
	- line 248: # TODO: add checking here, datatype casting may cause precision loss


vta/runtime/runtime.cc (1 line):
	- line 952: // FIXME: Right now memory_type is a 2-bit field which means that


vta/scripts/tune_group_conv2d.py (1 line):
	- line 157: # check_correctness=True, # TODO: re-enable when check_correctness works again.


python/tvm/micro/compiler.py (1 line):
	- line 148: # TODO use march for arm(https://gcc.gnu.org/onlinedocs/gcc/ARM-Options.html)?


vta/scripts/tune_conv2d.py (1 line):
	- line 162: # check_correctness=True, # TODO: re-enable when check_correctness works again.


python/tvm/relay/frontend/coreml.py (1 line):
	- line 38: # TODO: we need to support more colorspace, such as rgb.


rust/tvm-rt/src/object/mod.rs (1 line):
	- line 32: // TODO we would prefer to blanket impl From/TryFrom ArgValue/RetValue, but we


jvm/core/src/main/java/org/apache/tvm/NativeLibraryLoader.java (1 line):
	- line 40: * TODO: shutdown hook won't work on Windows


python/tvm/topi/cuda/sparse.py (1 line):
	- line 225: # TODO: ideally we could vectorize this


python/tvm/relay/op/contrib/tensorrt.py (1 line):
	- line 957: # TODO: (codeislife99) : Fix different dynamic batch size inputs


src/runtime/contrib/coreml/coreml_runtime.mm (1 line):
	- line 171: // TODO: Support multiple outputs.


python/tvm/driver/tvmc/autotuner.py (1 line):
	- line 216: # TODO (@leandron) This is a path to a physical file, but


python/tvm/relay/qnn/op/qnn.py (1 line):
	- line 346: # TODO enforce 4-way padding in topi/nn/conv2d after #4644 merged


vta/scripts/tune_dense.py (1 line):
	- line 119: # check_correctness=True, # TODO: re-enable when check_correctness works again.


python/tvm/topi/cuda/batch_matmul_tensorcore.py (1 line):
	- line 214: # TODO: add checking here, datatype casting may cause precision loss


python/tvm/topi/cuda/conv3d_winograd.py (1 line):
	- line 308: # TODO unrolling by omg, eps, nu may improve performance but


python/tvm/topi/x86/conv2d_avx_1x1.py (1 line):
	- line 235: # FIXME - https://github.com/apache/tvm/issues/3598


python/tvm/topi/arm_cpu/depthwise_conv2d.py (1 line):
	- line 152: # TODO:


vta/scripts/tune_resnet.py (1 line):
	- line 298: # check_correctness=True, # TODO: re-enable when check_correctness works again.


vta/python/vta/transform.py (1 line):
	- line 495: # FIXME: pad_value is ignored...


vta/tutorials/autotvm/tune_alu_vta.py (1 line):
	- line 122: # check_correctness=True, # TODO: re-enable when check_correctness works again.


python/tvm/topi/cuda/conv3d_ndhwc_tensorcore.py (1 line):
	- line 78: # TODO: add checking here, datatype casting may cause precision loss


src/runtime/opencl/opencl_device_api.cc (1 line):
	- line 120: /* TODO: the warp size of OpenCL device is not always 1


rust/tvm/src/ir/expr.rs (1 line):
	- line 91: // TODO: figure out how to type the last argument runtime::TypedPackedFunc<String(ObjectRef)> annotate)


python/tvm/topi/x86/conv2d.py (1 line):
	- line 270: # FIXME - https://github.com/apache/tvm/issues/4122


python/tvm/topi/nn/sparse.py (1 line):
	- line 269: # TODO: Add BSR transpose support


python/tvm/autotvm/task/relay_integration.py (1 line):
	- line 55: # TODO: Currently VM compiler is likely to stack overflow for large models.


python/tvm/relay/op/nn/nn.py (1 line):
	- line 220: # TODO enforce 4-way padding in topi/nn/conv2d after #4644 merged


python/tvm/topi/cuda/conv2d_nhwc_tensorcore.py (1 line):
	- line 75: # TODO: add checking here, datatype casting may cause precision loss


vta/scripts/tune_conv2d_transpose.py (1 line):
	- line 154: # check_correctness=True, # TODO: re-enable when check_correctness works again.


python/tvm/relay/op/strategy/arm_cpu.py (1 line):
	- line 179: # TODO:


apps/microtvm/zephyr/host_driven/src/main.c (1 line):
	- line 263: // TODO (mehrdadh): Update this when zephyr version has updated to 2.6.


python/tvm/topi/cuda/scan.py (1 line):
	- line 368: # TODO: add support for a prod_scan


rust/tvm-rt/src/array.rs (1 line):
	- line 171: // TODO: type check


src/relay/qnn/op/concatenate.cc (1 line):
	- line 169: // FIXME (anijain2305) - The lowering can be further optimized. Instead of inserting requantize in